May 1, 2024 • 46 mins
The tech industry has no shortage of buzzwords and jargon. Some of the terms common in tech are ones that people have come to hate for various reasons. From AI to blockchain to the metaverse, we explore buzzwords that drive some people bonkers.
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Speaker 1 (00:04):
Welcome to Tech Stuff, a production from iHeartRadio. Hey there,
and welcome to tech Stuff. I'm your host, Jonathan Strickland.
I'm an executive producer with iHeart Podcasts and how the
tech are you? So? Old time Star Trek fans may
both love and kind of cringe at the use of
(00:26):
some of the technobabble in scripts for that show. My
go to Star Trek tech Nonsense always includes the phrase
reverse the polarity, which typically doesn't mean very much in
most of the dialogue where it pops up, but it sounds,
you know, science adjacent. So I suppose, you know, we
should give writers some slack. They're trying to write stories
(00:46):
that are set in a far off future about technology
that really we can only dream about today. I still
want a replicator, though. Just look at how far the
tech world has come, however, since the original Star Trek
series first broadcast back in nineteen sixty. But you don't
have to go to the future to encounter plenty of
jargon and buzzwords. They're all over the place, particularly in
(01:07):
the tech sector, really throughout the business sector in general,
but tech in particular is incredibly guilty of this. It's
one of the hallmarks of tech, and you get extra
points if whatever term you're using is so vague or
easy to misuse that it may as well be meaningless.
So today we're going to talk about some tech buzzwords
(01:27):
that have made various lists for most hated buzzwords in Tech,
or most hated jargon in Tech, or something along those lines. Now,
I pulled these terms from a lot of different sources,
all from articles that were about hated or misused tech buzzwords.
Some of the buzzwords are used well beyond tech itself.
(01:48):
Some of them don't even originate from tech, but just
get reused. And I use sites like The American Genius
and Smart Company and CMC Global and DNS Research, Vation
and Forbes and trust Radius and net Suite to gather
all of these different terms. And the terms span the
last several years. Some of these buzzwords have faded a
(02:11):
little bit from use. We're going to talk about some that,
you know, just a couple of years ago were dominating
the conversations in tech, and now they're almost forgotten. Now
I'm going to start with one that I personally find exhausting,
and I bet a lot of y'all out there feel
much the same way, and that term is, of course
(02:33):
the biggest buzzword of the last couple of years in
tech Artificial intelligence, or more frequently, just plain old AI.
The explosion in AI development over the last couple of
years has really elevated the buzz terms use within the
tech space. And don't get me wrong, AI has been
a thing in tech for decades, like more than half
(02:54):
a century. It's a common theme in science fiction stories,
whether we're talking about comedic droi sidecakes, or you know,
some omnim present malicious intelligence determined to wipe out humans.
But in the last couple of years, AI has really
ramped up in the public consciousness, largely thanks to a
specific branch of the discipline, that of generative AI. Now
(03:18):
I don't think anyone out there is unfamiliar with generative
AI at this point, but just in case this term
is new to you, Generative AI creates stuff. It generates
based upon user input. So you might ask a question
and then it gives you an answer, or you might
create a suggestion that it makes some sort of content
like I once tried to use generative AI to make
(03:41):
I think it was a Shakespearean sonnet about artificial intelligence,
and it did a decent job at making a very
clever poem about AI, but it didn't follow the Shakespearean
sonnet rules, and I'm a stickler for form. Anyway, you
could even have generative AI that can create images based
on techs. You're all familiar with this, I'm sure, and
(04:03):
even today you can get to the point where you
can create video clips with some of these forms of
generative AI. And there's no doubt about it. Generative AI
can be really impressive, at least when it's working properly.
When it's not working properly, it can be creepy or unsettling.
Sometimes it could be like that if it's working properly too,
don't get me wrong, but man, even as recently as
(04:25):
just a couple of weeks ago, I was using an
image generator out of curiosity, just trying to create images
of characters from a friend of mine's podcast. She made
this podcast, and I was just like, I wonder if
I could create some like character concept images. And I'm
not an artist, and I just did this out of curiosity,
having no desire to actually use the images, but I
(04:47):
was wondering if I could make it happen, and still
fingers are hard for AI, y'all. There were so many
love crafty and monstrosities created by this image generator, and
it made me really feel calm that if I were
to actually help my friend create character images for some
of her creations, I would actually work with an artist.
(05:10):
I would hire a human artist to work with, because
then I know I would be one helping an actual
artist get work, which I think is really important and
to get what I wanted. But countless startups have launched
since late twenty twenty two, when open ai really got
the ball rolling by introducing chat GPT. Though to be clear,
(05:30):
there were already some generative AI applications available before chat GPT.
I would just say chat GPT launched everything into the stratosphere.
But here's my problem. Generative AI is just one implementation
of artificial intelligence, and it's not the only kind. AI
is actually an enormous discipline. It covers a huge amount
(05:52):
of ground like computer vision and image recognition that falls
under AI. Natural language processing is part of AI, and
obviously it has to be part of generative AI too.
If you're going to get anything that even resembles what
you were asking for, a lot of robotics falls under
the category of AI. Not all of it, but a
lot of it does. And on top of that, you
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know the fact that we have all these different kinds
of AI and not just generative means that using the
blanket term the umbrella term for one specific implementation is
really not very accurate. But on top of that, some
companies are using AI pretty liberally to cover stuff that's
not even really artificial intelligence, like stuff like just algorithms.
(06:36):
And yes, algorithms are part of AI, they can be
part of AI, but that doesn't mean an algorithm by
itself should be described as AI. So if you've got
an algorithm that is looking at what I'm browsing, you know,
I'm looking at maybe vinyl record albums of the New
York Dolls, and then it do you have a recommendation?
Algorithm says, hey, maybe you should check out Velvet Underground.
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That's not exactly artificial intelligence, although it is an excellent suggestion.
But because AI is so buzzy, right, it's such a
popular buzzword, there have been this ton of startups that
have begun to use AI to describe their pitch to
investors and to media. I can't tell you how many
unsolicited emails I get every single day from PR firms
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representing clients who are trying to position their business as
the next big thing in AI, and sometimes, in fact,
I would argue frequently, they have little to no connection
to the actual discipline of artificial intelligence. On top of that,
I am also frustrated that so many businesses seem anxious
to jump into AI or else. I guess they're worried
(07:45):
they'd be left behind, but it seems to me that
many of these businesses have very little to no strategy
that's actually connected to AI. It's almost as if the
idea of AI is some sort of fix all solution
to every problem. That is going to be probably the
coda for this podcast. The motto of this is that
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there are these buzzwords that people use, and it's almost
like a shortcut or a get out of jail free card,
where you've got this problem or challenge or goal in mind,
but you have no idea how to achieve that goal,
or overcome that challenge or solve that problem, So you
just use this kind of blanket term to stand in
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place of an actual solution, and then you're just magically
where you need to be, and we all know that's
not really how the world works. I wish it were.
I would love to be able to use that kind
of logic to fix all sorts of things in my life,
but that's just not how it works. And you know,
you can't just open a big old box that has
the label AI on it and then business will magically
perform better. It's kind of like how I am with
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electric guitars. So rather than practice on the electric guitar
I literally have standing right next to me. Sometimes I think,
you know, I should really buy a new guitar, as
if some how that new guitar is magically going to
make me a better player. And I can tell you
from experience that doesn't work either. And also my partner
would likely kick me out of the house if I
try and do that again. So I think the four
(09:12):
guitars I have are enough. Before we move on, we
should lump in some other AI related terms in here,
because AI, while that one alone is extremely buzzy and
people misuse it or you know, misinterpret it all the time,
there are others that fall into that same general category,
like machine learning and deep learning. They do have meaning.
(09:33):
These terms actually do mean something, so does AI for
that matter. They have meaning and they have relevance, but
they are frequently overused or misused by various tech companies
out there. And that's not good because you know, it
can set unrealistic or incorrect expectations, and then when those
expectations aren't met because the person had the incorrect interpretation
(09:54):
of what the terms actually meant, then support for research
and development in those kinds of fields can decline. And
I know that sounds kind of dramatic, but it's happened
again and again and again. It happened with virtual reality.
You know, we're seeing it possibly happen with mixed reality.
If someone's working on a research project and then they
find out that their funding has been cut because the
(10:16):
people who are in charge of the purse strings had
the wrong idea of what your work actually is all about.
And then once they find out what it is about,
they're like, oh, well, that's not what I wanted and
they cut off funding. That stinks, right, That really did
happen with VR in the nineties. You had people who
are working on important implementations of VR. I'm not talking
just like games, which I mean, I think games are important,
(10:39):
but beyond that, using VR for things like treating mental illness,
and then all the money for research kind of dried
up because people were disillusioned with what VR actually was
compared to what they thought it was. This stuff happens, Okay,
Next up, I want to talk about disrupt and disruption.
So these terms have been around for a while, and
(11:00):
it's a dramatic word. Typically, it just means that someone
has figured out a new way to do something. Sometimes
it's not even a new way. Sometimes it's just a
way that's a little bit different from how everyone else
is doing it currently. But it might be a very
old way that just fell out of favor and then
you kind of resurrect it. Now, the implication of disruption
is that this new way of doing things is going
(11:21):
to upend the industry it's in as a whole, and
that it will threaten the security of companies that refuse
to adjust to this new method and it will leave
them in the dust if they're unable to adapt. And
it's easier to understand if we just consider a couple
of examples. Amazon, for instance, disrupted retail. But how did
it do it well? It did retail online starting with
(11:43):
books and then eventually encompassing pretty much everything you can imagine.
And I would argue that Amazon really isn't that much
different from other huge retail companies in that many of
the strategies employed by Amazon are similar to ones that
were honed by companies like Walmart. It's just that Amazon
cut out the brick and mortar stores for the most
part and employed some other technologies to personalize the experience. Plus,
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you know, buying stuff online means people don't have to
interact with other human beings, and for a not insignificant
slice of the population, that is a huge selling point.
Oh I don't need to talk to a person, I'll
just buy it online. Uber Lift and other ride haling
companies disrupted the taxi industry, which obviously has been a
real sticking point in various places around the world where
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taxi companies have a great deal of influence. We've seen
examples of local governments cracking down on these kinds of
startups for sidestepping regulations that the taxi industry must obey,
and there have been attempts to refer to these as
ride shares, but because it's actually all about funneling money
through to the parent organization like Uber or lyft or whatever.
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It's not really ride sharing, it's ride haling, so it
really is more like a taxi service than say, just
connecting people who happen to want to get to the
same place the same time. And there are a lot
of other examples. Of course, Airbnb is disruptive to not
only the hospitality industry but also real estate. I mean,
it's hard for folks who are just starting out to
go out and buy a house when the market caters
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to rich people who want to add to their portfolio
of rental properties. But not everything that's being called disruptive
is actually upsetting apple carts. Sometimes the things that are
being called disruptive are just a new kind of business.
Sometimes it's describing a way of doing things that's different,
but it's not necessarily advantageous compared to how the industry
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as a whole is doing whatever the thing is. And
a lot of leaders really hate the term disruptive because
it can distract folks into pursuing disruption at the expense
of actually making a business model that works. If you're
banking on everything causing disruption in an established market and
you're not actually spending effort making sure that your approach
even makes sense. You're just trying to watch the world burn.
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Related to disrupt is the term game changer. That phrase
implies that the business model forces a change on an
entire industry, it changes the game. That very rarely happens. Instead,
we often hear game changer applied to businesses that are
just new, even ones that aren't doing anything particularly that
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differently from their competitors or performing better than their competitors.
Sometimes they're performing worse. That's hardly changing the game. Okay,
we've got tons of other buzzwords to get through. Before
we do that, let's take a quick break to thank
our sponsors. We're back. Time to talk about some more
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buzzwords that get a lot of hate on these lists.
This next one is a huge one. It sometimes ranks
is number one depending upon the year, and that is
digital transformation that popped up on multiple most hated buzzwords
and tech lists. John Moore of tech Target first this
definition of digital transformation. He says, it is quote the
(15:05):
incorporation of computer based technologies into an organization's products, processes,
and strategies. Organizations undertake digital transformation to better engage and
serve their workforce and customers and thus improve their ability
to compete end quote. So it's kind of like modernizing really,
(15:26):
is what I would call it. You know, you're trying
to figure out how can we take these various legacy
systems and processes and bring them into the digital age,
potentially making things easier to manage and monitor and measure
and all those sorts of things. Cindy Jondon of IFS,
which is a cloud computing company, says, quote, it's really
(15:48):
a seismic shift forcing organizations to better enable their teams
and improve asset usage and customer experiences end quote. To me,
that's teetering pretty darn close to being too vain to
be really useful. But at the same time, you could
argue that each organization is going to have its own
specific set of requirements and challenges, and so therefore it's
(16:09):
impossible to get specific, right because if you get specific,
then you're leaving out lots of other use cases, so
you have to be really general. But yeah, that particular
description to me borders on not being very useful. Now,
as pointed out on CMC Globals site, and issue with
the concept of digital transformation is that there's a tendency
(16:31):
to treat it again as a magical panacea similar to AI,
right that by somehow just porting processes over into a
computerized system, maybe even one that's networked, based on the cloud,
whatever it may be, you have somehow transformed the business inherently,
even though it's the exact same processes and everything, it's
just now it's done in a different way. Business strategy
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is still absolutely important, and without business strategy, shifting how
you do things from one model to another doesn't actually
address fundamental issues. Again, it's like you're slapping a band
aid on something and you don't even understand it. It's
like if someone had a cold and you put a
band aid on their arm doesn't really address the problem.
There's no denying that modernizing systems so that they're more
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easily accessible and adaptable is really important. But as Mark
Bilger of One Call puts it, quote digital transformations do
not magically transform the business. A fool with a tool
is still a fool, end quote. Kind of dig that.
There are a lot of companies out there that do
consulting work on digital transformation. I'm sure some of them
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are quite good at it, but in my experienced consultants
are the absolute worst when it comes to leaning on
buzzwords in jargon to obfuscate what they mean. And I
feel like I can say that with some authority because
in my previous professional life, before I ever worked for iHeart,
before I work for Discovery Communications, before I work for
house stuffworks dot com, I spent more than seven years
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working for management consultants. And I've read a lot of
proposals and a lot of reports, y'all, And one thing
I walked away with is that consultants just love to
use language that ultimately doesn't mean very much but sounds good.
Another big buzzword that makes these lists, and it's been
around for quite some time at this point, is the cloud. Now,
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there's a meme that goes around that is one hundred
percent accurate that says there is no cloud, It's just
somebody else's computer. That's true. That's the basic truth of
what the cloud is. Cloud computing, cloud storage, cloud development,
whatever cloud service you're talking about. Ultimately, these all describe
a situation in which the thing you are using is
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a computer system that's provided by a third party, and
that's it. That's the magic of the cloud. So It
may be that it's an operating environment. It may be
that it's you know again, storage. It could be any
of those things. But really it just means that these
these services are living on computers that are some else. Now,
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cloud solutions free up businesses so that they don't have
to host their own services on premises or in tech speak,
on prem. I cannot tell you how much I hate
on prem not the concept but the actual use of that,
as if on prem is somehow saving you a huge
amount of time as opposed to saying on premises. In
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my humble opinion, on prem is just a way to
create a code language that in small ways excludes outsiders
from your group. It's kind of akin to the Little
Rascals having the he Man Woman Haters Club, though I
really guess only a fraction of y'all probably know who
the little Rascals are. I'm old, but anyway, my commentary
aside the issue many take with cloud terminology is that
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people will frequently use the phrase, similar to what we
saw with AI and digital transformation, that it's some kind
of cure all for any business challenge. There are definitely
really good reasons to use cloud services, right like you
might not be able to scale your services to your
customers if it became really popular. Right, if you host
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everything yourself and everything's running on servers that are in
your own office space or garage, whatever it may be,
and you suddenly get really popular, you could end up
having your service completely overwhelmed and now you can't provide
services to anybody. And this is also kind of a
good problem to have. It means that your services are
resonating with customers, but you don't want the experience for
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them to be to log in and find out they
can't access the thing that they're paying for. That's bad.
So leaning on a large, established cloud provider could be
the solution. It might be that, oh, well, we can
scale just by purchasing more compute power or more storage
from this provider. But just poorting stuff from your own
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systems to the cloud doesn't automatically make them work better
or reach more customers. It's not like the company providing
the cloud services is going to be doing your marketing
for you or anything, because they've already got their customer.
Their customer is you. It's your job to go out
and get your own customers. But yeah, cloud computing is
often used as sort of this hand wavy way of saying,
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don't worry about these problems, we got it covered, when
in fact, the cloud does not magically solve stuff on
its own. Again, this is a real issue with a
lot of these buzzwords. If I'm being honest, it's really
it's not the word's fault necessarily, it's that folks are lazy.
People are lazy and they don't want to have to
really tackle and define the real challenging business or tech
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issues that they're facing. That's hard. This is very hard
to actually identify and then solve these tough business problems.
It's really hard work. So it's way easier to just
use a phrase or a term and to take a shortcut,
especially if you're an executive, and then you foist the
actual problem onto your underlings and it's their job to
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actually figure out, Okay, well, how do we do the
thing that our boss wants us to do when all
our boss says is cloud compute or digital transformation. To me,
this is kind of like the underpants gnomes in South Park,
You know the underpants domes. They say phase one is
collect underpants, phase two is something, and phase three is
profit that's what a lot of these buzzwords are. You know,
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the buzzwords are phase one, Phase two is completely undefined,
and then phase three is somehow huge success. And I'm
sad to report again it usually does not work out
that way. All right, So what's next? Well, I guess,
I mean, I didn't want to have to do this
because I really don't like covering these kinds of things,
but it's time to tackle blockchain and the related buzz
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terms around that. So blockchain is a thing, right, I'm
not saying that blockchain doesn't mean anything. It absolutely does
mean something. It's mostly a thing that people associate with
cryptocurrencies because that's where it's seen the most use and
I would argue the most success. But blockchain evangelists proclaim
that blockchain is going to underpin the entirety of the
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Web of the future. This will play into a another
buzz term we'll talk about shortly, web three. Now, these
evangelists aren't always super good at articulating how blockchain will
actually underpin the web of the future, just somehow that
it will, and often a lot of details get glossed
over in the process. I mean, blockchain has a lot
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of challenges facing it too, Like a lot of those
systems are very slow, they're inefficient, some of them are
extremely thirsty for electricity if it's based on a proof
of work approach to blockchain. So there are a lot
of issues that evangelists usually don't directly address, and they
have pretty glib answers if you start asking follow up questions.
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But what does blockchain actually mean? Well, basically, a blockchain
is a record of transactions. Typically we're talking about a
decentralized ledger, meaning this ledger does not exist in any
one given computer, it is distributed across lots of different computers,
and this ledger is a record of all these transactions.
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And not only is it a record, it's viewable by
a collection of stakeholders. So in some cases those stakeholders
could be everyone who is connected to and is using
the system. So in other words, it's as public as
it gets, right, as long as you are part of
the system, you can actually view the ledger. But in
other cases, we could be talking about a closed blockchain
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and which only a select number of parties have access
to that ledger, even if the blockchain itself is a
foundation for a service that lots of other people are using.
So you might have tons of people using, say a
specific cryptocurrency, but only a small collection of stakeholders are
able to actually view the ledger itself. That is problem
number one. Actually, often I hear or read about projects
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that are pitched to be built on top of a blockchain,
and the implication is that this makes the system inherently transparent.
It doesn't. For example, there was Facebook, which is of
course now called Meta, and Facebook's attempt to ch a
cryptocurrency initially called Libra, later it was called DM. Actually
technically Libra itself was I think the second name for it,
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but Libra and then DIM. The blockchain serving as the
foundation for this particular cryptocurrency was going to be the
domain of a consortium of companies that initially was called
the Libra Association, later became the DM Association. So instead
of a community of users all having access to this
distributed ledger of transactions, it would be this consortium. But
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that ultimately did not work out. The whole project got
bogged down, a ton of companies that initially had signed
on to be part of the consortium bailed on it. Ultimately,
the consortium sold off what few assets it still had
to a bank called Silvergate Capital for a couple hundred
million dollars. At least that was the belief. The money
amount was never made public, but then Silvergate subsequently shut
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down the following year. Because this stuff is hard, y'all.
I mean, if Facebook can't do it, it's really hard.
We'll come back to that when we talk about the metaverse. Anyway,
the selling point for blockchain technology is that the record
of transactions is both transparent and it is reliable because
each block of transactions is cryptographically linked to all the
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previous transactions in that ledger, and we'll be linked to
all subsequent transactions in that ledger. And this means that
no one can tamper with the records of previous transactions.
If you went back and tried to change the record
further back on the list, like let's say it's three
blocks back, well, that would actually make changes to the
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next two blocks. It would be impossible to hide. So
there's no bacxies. Every transaction is permanent. You know, you
could do a new transaction with the exact same assets,
right Like if you had purchased something and then you
wanted to turn around and sell it you could do that,
but you couldn't purchase something and then go back and
erase the record of you purchasing it so that you
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magically get your cryptocurrency back. You can't reverse an earlier
transaction that way. So this leads some to say, aha,
we can use blockchain to serve as the bedrock for
all online transactions. I mean, you could do it to
keep record of like buying a house. You know, you
enter that transaction into a blockchain that shows proof of
this transition of ownership of the property. No one else
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can claim to own your property. You've got the record
right there, and it is unalterable and irreversible. So the
blockchain will show that the transaction happened and will serve
as proof that ownership has changed hands. Moreover, it can
serve as a record for digital transactions, which are a
lot more whibly wobbly than stuff that you can buy
and sell an actual meat space. So, for example, let's
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say I wanted to buy a clip of music. Maybe
I even want a smart contract that gives me the
license to use that music clip in some other work,
such as an episode of a podcast. Well, you could
set that up on a blockchain ecosystem to show proof
of this transaction, and that could stand as the record
indicating that I, as a customer, have legally purchased the
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license to use a clip of someone else's music in
my work. Now that's just one hypothetical example. This does
tie into n fts or non fungible tokens. But there
was obviously a huge problem with NFTs as they rolled out, Namely,
they became a target for insane and unsustainable speculation. So
folks were buying up NFTs with the expectation that these
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digital assets were going to escalate in value, and a
lot of companies got in on the NFT craze. They
saw it as a way to essentially print money, or
they were afraid of being left behind, and ultimately the
NFT bubble popped and laid waste to the entire landscape,
and it also did an enormous amount of pr damage
to the NFT concept as a whole. So even folks
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who were coming up with undeniably interesting ideas for NFTs
found themselves scrambling for interest and support because the speculative
market had burned so many people. Okay, we're coming up
on the last third of our podcast and speaking of thirds,
we'll be talking about Web three next, but first let's
take another quick break to thank our sponsors. All right,
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we're back and we're going to talk about web three now.
A lot of the buzzwords we've talked about so far
have an actual meaning, right, They do have meaning to them,
but often there's this issue of people misinterpreting or misusing
the terminology, misconstruing something, and then the meaning of those
(29:31):
other terms gets a little fuzzy. Web three is not
like that, though, because it doesn't really have a definition.
It's kind of like the term metaverse, which we will
talk about in a second. In fact, I would argue
web three and metaverse are very similar in that regard.
They are both words used by people to make some
pretty vague statements about a kind of hazy future of
(29:53):
online interaction and commerce and society. But once you start
to dive down into it, you start to discover that
there actually are a lot of different takes on what
these things are ultimately going to be, and so it
doesn't seem like anyone's really on the same page, Like
there are a lot of similarities, but there are a
lot of differences too, and this ultimately means there's not
(30:15):
a really meaningful way to talk about these kinds of things.
But you still have companies jumping on board in an
attempt to establish a presence in an undefined field or
else lose some sort of unknowable advantage. So generally speaking,
most versions of Web three share certain qualities. One of
the big ones is decentralization. So a big criticism of
(30:37):
the current web is that power and influence gravitates toward
a few massive players in the space. We're talking big
companies like Amazon and Google, for example, and there's no
denying it, Like, there are certain companies that have a
stranglehold on the massive amounts of data that pass over
(30:57):
the Web, And so the thought is, wouldn't it be
better if we democratize that power somewhat? We took it
so that the next version of the Web is not
entrusted into the hands of these corporate mega giants, but
rather to the users. You know, that's what evangelists like
to say, put the power in the hands of the users,
which is kind of like tron. Critics of Web three
(31:20):
say that most of the Web three implementation ideas would
really just create different power brokers for the Web. It
wouldn't be the big companies that we talk about, the
big tech companies, but it would go into the hands
of a wealthy subculture that would be able to afford
to act as the cornerstones of this new web. So
really it doesn't democratize who owns the web. It just
(31:41):
designates different stakeholders, the folks in charge of overseeing the
various systems that Web three is actually built upon, which
usually involves some kind of blockchain technology and token economy.
Now I don't mean a token economy. I mean an
economy based upon the minting, buying, selling, and trading of
digital tokens. And we heard a lot of buzz about
Web three just a couple of years ago. And to
(32:03):
be clear, there are still companies that are working toward
making something along the lines of a Web three implementation happen.
But the excitement around this has fizzled out quite a bit.
And I honestly I think that artificial intelligence has managed
to drink an awful lot of tech milkshakes. So you
can also look at the metaverse as an example of this,
(32:25):
where some of that excitement has been ported over for AI.
In fact, according to Gopal Solanki, who wrote a piece
on Medium that's titled is Web three dead already? He
said investment in Web three companies has fallen by more
than seventy five percent in twenty twenty three compared to
the levels it had in twenty twenty one. He went
(32:45):
on to say, we cannot say that Web three is dead,
but it has surely failed to deliver the promises it made.
Each innovative idea presented in the form of renovated web
version has turned into complete dust on unless it has
something to do with the native cryptocurrency token. All the
developments and projects introduced in the Web three hype are
(33:07):
majorly underperforming. That seems to sum it up to me.
I can't disagree with that, and not to say that
something called Web three won't come down the line, but
in the meantime, that term is largely without meaning, and
it's mostly used by people who are scrambling for funding
for something that's unproven and potentially no better than what
(33:30):
we already have. In fact, potentially it could be worse.
Things like transmission speeds and stuff could be drastically affected
because again, blockchain transactions are not the most efficient. So
if you build everything based on blockchain transactions like online
commerce is completely based on blockchain. It could mean that
it's just overwhelmed that it's far too slow to deal
(33:54):
with that level of responsibility. All right, Well, then let's
tackle metaverse and mixed reality, more stuff that went through
the hype cycle and recently has struggled to remain relevant.
Starting off with the metaverse, we're talking about a concept that, again,
like Web three, does not have a firm definition. There
are a distinct lack of details. Generally speaking, most definitions,
(34:17):
if you can call them, that, imply a persistent virtual
world in which you can explore and socialize and shop
and create and consume, kind of like a computer generated
alternate reality to the reality we experience if we step
outside our houses. Some versions of the metaverse tap into
similar stuff that we hear about in Web three, like
(34:40):
cryptocurrencies and blockchain. Other versions of the metaverse focus more
on the virtual reality aspect and things like creating your
own avatar and being able to maneuver around these virtual environments.
Some versions of the metaverse describe a huge, interconnected series
of virtual worlds kind of hosted by different intit so
(35:00):
there might be one that's owned and operated by Meta
and another one owned and operated by Amazon, and maybe
they're interlinked together so you can pass through from one
to the other, kind of like how the web itself
is a big interconnected series of web pages, but instead
you're talking about a virtual world with like three dimensional
virtual space, but like web three. A lot of the
(35:22):
enthusiasm and excitement around the metaverse has kind of gone
cup put in recent years. There was a flurry of
excitement about the metaverse idea for a while, and you
had people and companies that were rushing to establish a
presence on various platforms, claiming that these platforms would become
pillars of the upcoming metaverse. But you don't hear about
(35:42):
that as frequently these days. It kind of blows my
mind that virtual real estate sold for real money, sometimes
a significant amount of real money, even before any such
platform had established itself, as you know, a real thing
that people wanted to go and spend time at. It's
kind of like this wild land rush, except land in
(36:03):
the real world is a finite resource, and the only
thing stopping yet another company from launching a virtual real
estate company is computational hardware. Scarcity is not really a
thing in the digital space, which again brings us back
to the challenges of digital assets and transactions anyway. Obviously,
there are still companies that are working on creating a metaverse,
(36:24):
but the question I have is how many folks are
actually itching for a metaverse. I wondered that from the
very beginning. I definitely wonder it. Now. Meta has spent
billions with a b of dollars on such efforts. It
continues to do this, much to the chagrin of investors,
and I am still not convinced that those efforts will
have a good return on investment. Maybe we'll get some
(36:46):
virtual environments out of it, and some of them might
even be really good and compelling experiences, but I don't
know that that's going to be enough to get the
results needed to make those billions of dollars a sound investment.
I don't know if it's going to make that, you know,
the metaverse the future of online interaction. But then again,
I'm not a genius anyway. There are tons of barriers
(37:08):
that the metaverse will have to overcome in order to
become a real thing. And real thing you can put
in air quotes. I guess, assuming that you know it
does involve virtual reality. One of the hurdles for the
metaverse is the cost to the consumer, because VR headsets
aren't cheap. Now, there are some headsets that are significantly
less expensive than earlier models, so they aren't necessarily as
(37:30):
expensive as they used to be, but they're still not cheap.
And computers are really versatile technologies, right, You can do
a lot of stuff on a computer. Now, you could
arguably do most of that same stuff, if not all
of it, while wearing VR gear as well, But that
requires a lot of work to design a really good
user interface so that the person who's wearing the VR
(37:51):
gear can do whatever it is they want to do
in a way that makes sense and feels natural. But
if you can already do pretty much all of that
stuff on a computer, you know, with the exception of
being in an immersive virtual environment, I'm not sure the
sales pitch is good enough to get people to buy in. Also,
this whole concept of an online world that is persistent
(38:11):
and virtual and even three dimensional isn't new. Folks have
been talking about that for years. Heck, you watch old
Hollywood films that represent the web, and it almost always
has someone seeing at a computer, and it looks like
they're playing some sort of weird first person shooter navigating
through stuff, because that looks way more exciting than just
staring at a page full of text and hyperlinks. Right,
(38:34):
But you know, navigating through a virtual space in order
to get to a destination has never made much sense
to me. Like, instead of having websites, having you know,
maybe like a virtual mall of stores and you have
to wander around in order to go to places, that
just doesn't make sense. Clicking on a link is super
fast and efficient, and sure you could build that kind
(38:54):
of capability into the metaverse, you know, maybe you make
it a voice command. But is the experience of just
teleporting from one virtual spot to another, perhaps, you know,
just to do some shopping, or maybe even just check
the news. Does that really sound like an experience most
people want to have, because I think it would be
pretty disorienting and distracting and inefficient. You could do it
so much faster just using a computer or a smartphone.
(39:16):
But really, whether you think like I do and you
find the whole metaverse concept puzzling, or if you think
it's a great idea, there's no getting around that. Tons
of folks and companies. We're using metaverse as shorthand for
this is the future. Nearly every press release or announcement
I saw relating to the metaverse said very little apart
from we're forward thinking and we're super cool, without you know,
(39:39):
doing anything to back up those claims. Just as cloud
computing and digital transformation can be used as buzzy shortcuts
to avoid addressing real challenges, I feel like the metaverse
and web three come across as more or less meaningless
terms used to proclaim relevance. You know, they might not
be anything today, but maybe tomorrow. Right, you'll see and
you'll see it from us, because we're hip and we're
(40:01):
with it. Okay, I'm really old, So maybe I'm just
way too cynical. Maybe it's brought on by the fact
that a lot of early attempts at showcasing ideas that
are at least intended to be incorporated into the metaverse
have been a bit disappointing. This brings me to mixed
reality now, y'all. I love me some mixed reality. I'm
(40:21):
not as big on VR these days. I acknowledge that
VR is the far more successful end of the mixed
reality spectrum. VR at least has established use cases in
the form of gaming. My problem is physiological because as
I get older, I get more prone to motion sickness,
which stinks. It's not the technology's fault necessarily, unless latency
(40:42):
is really bad, in which case it is the technology's fault.
But you know, I used to be the guy who
would ride a roller coaster two dozen times in a
day and think nothing of it. Now, if I ride
two different roller coasters in a row, I have to
lie down for forty minutes, So that's on me. But
VR has a place at the table, right It's an
established technology, and there are some great VR games and
(41:04):
experiences out there. It's still not necessarily a large enough
library of experiences to get a critical mass of users
on board, but the audience for VR tends to be
fairly enthusiastic or at least curious to try VR stuff.
I do know a few people who have VR setups
that have gone untouched for you know, long enough for
them to gather dust, So I don't know how common
(41:25):
that is. I'm sure there are people who use it
every day, you know. I've got a friend who uses
VR to do exercise with beat saber and that's you know,
she's not alone. Lots of people do that. It's on
the augmented reality side where I am actually the most interested.
But I simultaneously have to admit that not nearly enough
has been done in the AR space to make it
(41:46):
really useful outside of some very specific implementations. And I
think it's easy to imagine how AR could be useful,
Like if you can overlay digital information on your view
of the real world around you. There are countless ways
to make that really useful, everything from just entertaining to
genuinely answering questions or letting you do things more efficiently.
(42:07):
But while the technology has potential, we haven't really seen
that potential realized, and it's been a challenge so difficult
that even Apple appears to be struggling with it. Apple
launched the Vision Pro earlier this year. The year in
question is twenty twenty four for many of y'all listening
from the future. An initially word was that despite the
incredibly hefty price tag of three thousand, five hundred dollars
(42:29):
for the base model of this headset, the company was
actually going to sell out of its initial production run. However,
it's just a few months later and the story has changed.
An Apple analyst named Ming chi Quo posted that the
company was cutting orders by nearly half for the rest
of twenty twenty four, downgrading the expected unit sales that
(42:50):
initially were projected to be seven hundred to eight hundred
thousand units down to four hundred thousand to four hundred
and fifty thousand, which is a big old' oof because
demand dropped very quickly. Wes Davis of The Verge posted
an article recently that said he was finding listings on
eBay in which the headsets were selling for far below
market price, and Davis says it stings to know that
(43:11):
he could have waited and purchased a Vision Pro for
much less than what he actually paid for it when
it first became available. But really, I would argue that's
just the tip of the iceberg for consumer pain when
it comes to mixed reality, because I think the real
problem is that, facing a lack of a really big
user base, developers don't have a lot of reason to
make applications for AR hardware, because why would you spend
(43:35):
your time and your energy and your skills making something
that hardly anyone is going to get to use? But
if developers don't embrace the hardware, then consumers don't really
have an incentive to shell out the considerable amount of
money it costs to buy one of these headsets. It's
a catch twenty two issue, right because I don't want
a vision pro because I feel there aren't enough applications
(43:56):
for it. But no one's going to build applications for
the vision proh because people like me don't want to
purchase one. And then it's very possible that Apple will
either have to scale the tech way back so it
can introduce a significantly less expensive headset, which presumably would
have far fewer features and make it less attractive, or
just back away from the effort entirely and say this
(44:19):
one is a loss. My whole point is that if Apple,
with its famous reality distortion field, can't get mixed reality
to work in the market, it might just be too
early for that technology to take hold. Now, maybe someday
it'll be a big success, but it's going through its
own rough time, kind of similar to how VR really
struggled after a similar issue in the nineteen nineties after
(44:44):
that hype cycle kind of deflated. And this brings me
to a conclusion as well as a general warning that
I think it's really good to remember. If someone is
pushing very hard to sell you an idea, whether that
idea is AI, it's web three, a blockchain, or the
metaverse or mixed reality or anything like that, it often
(45:05):
indicates that the person talking to you is heavily invested
in that particular technology, and in order for their investment
to pay off, they need to get other folks to
buy into it. Now, I don't mean to say that
all of these ideas are ultimately nothing more than a
pyramid scheme, but they sure do operate that way in
the early days, and you don't get paid out unless
(45:27):
folks lower down the chain buy in. So buyer beware
is what I'm saying. Use critical thinking, make sure you
ask questions and make sure that the answers are satisfying
and that they mean something, and it's not just filled
with buzzwords and jargon. And for the leaders out there,
really think about different ways you can communicate your ideas
that aren't necessarily reliant on buzzwords, that actually do define
(45:51):
challenges and problems and solutions, because otherwise it starts to
sound like you're using language to cover the possibility that
you don't know what you're doing, and that's not a
good look at all. Doesn't serve anyone well in the
long run. All Right, that's it. Like I said, there
are tons of other buzzwords that we could include here,
(46:13):
and maybe I'll do another episode in the future with
more of these, but I thought this was a good
roundup for an episode like this. I hope you are
all well, and I'll talk to you again really soon.
Tech Stuff is an iHeartRadio production. For more podcasts from iHeartRadio,
(46:37):
visit the iHeartRadio app, Apple Podcasts, or wherever you listen
to your favorite shows.
Welcome to Tech Stuff, a production from iHeartRadio. Hey there,
and welcome to tech Stuff. I'm your host, Jonathan Strickland.
I'm an executive producer with iHeart Podcasts and how the
tech are you? So? Old time Star Trek fans may
both love and kind of cringe at the use of
(00:26):
some of the technobabble in scripts for that show. My
go to Star Trek tech Nonsense always includes the phrase
reverse the polarity, which typically doesn't mean very much in
most of the dialogue where it pops up, but it sounds,
you know, science adjacent. So I suppose, you know, we
should give writers some slack. They're trying to write stories
(00:46):
that are set in a far off future about technology
that really we can only dream about today. I still
want a replicator, though. Just look at how far the
tech world has come, however, since the original Star Trek
series first broadcast back in nineteen sixty. But you don't
have to go to the future to encounter plenty of
jargon and buzzwords. They're all over the place, particularly in
(01:07):
the tech sector, really throughout the business sector in general,
but tech in particular is incredibly guilty of this. It's
one of the hallmarks of tech, and you get extra
points if whatever term you're using is so vague or
easy to misuse that it may as well be meaningless.
So today we're going to talk about some tech buzzwords
(01:27):
that have made various lists for most hated buzzwords in Tech,
or most hated jargon in Tech, or something along those lines. Now,
I pulled these terms from a lot of different sources,
all from articles that were about hated or misused tech buzzwords.
Some of the buzzwords are used well beyond tech itself.
(01:48):
Some of them don't even originate from tech, but just
get reused. And I use sites like The American Genius
and Smart Company and CMC Global and DNS Research, Vation
and Forbes and trust Radius and net Suite to gather
all of these different terms. And the terms span the
last several years. Some of these buzzwords have faded a
(02:11):
little bit from use. We're going to talk about some that,
you know, just a couple of years ago were dominating
the conversations in tech, and now they're almost forgotten. Now
I'm going to start with one that I personally find exhausting,
and I bet a lot of y'all out there feel
much the same way, and that term is, of course
(02:33):
the biggest buzzword of the last couple of years in
tech Artificial intelligence, or more frequently, just plain old AI.
The explosion in AI development over the last couple of
years has really elevated the buzz terms use within the
tech space. And don't get me wrong, AI has been
a thing in tech for decades, like more than half
(02:54):
a century. It's a common theme in science fiction stories,
whether we're talking about comedic droi sidecakes, or you know,
some omnim present malicious intelligence determined to wipe out humans.
But in the last couple of years, AI has really
ramped up in the public consciousness, largely thanks to a
specific branch of the discipline, that of generative AI. Now
(03:18):
I don't think anyone out there is unfamiliar with generative
AI at this point, but just in case this term
is new to you, Generative AI creates stuff. It generates
based upon user input. So you might ask a question
and then it gives you an answer, or you might
create a suggestion that it makes some sort of content
like I once tried to use generative AI to make
(03:41):
I think it was a Shakespearean sonnet about artificial intelligence,
and it did a decent job at making a very
clever poem about AI, but it didn't follow the Shakespearean
sonnet rules, and I'm a stickler for form. Anyway, you
could even have generative AI that can create images based
on techs. You're all familiar with this, I'm sure, and
(04:03):
even today you can get to the point where you
can create video clips with some of these forms of
generative AI. And there's no doubt about it. Generative AI
can be really impressive, at least when it's working properly.
When it's not working properly, it can be creepy or unsettling.
Sometimes it could be like that if it's working properly too,
don't get me wrong, but man, even as recently as
(04:25):
just a couple of weeks ago, I was using an
image generator out of curiosity, just trying to create images
of characters from a friend of mine's podcast. She made
this podcast, and I was just like, I wonder if
I could create some like character concept images. And I'm
not an artist, and I just did this out of curiosity,
having no desire to actually use the images, but I
(04:47):
was wondering if I could make it happen, and still
fingers are hard for AI, y'all. There were so many
love crafty and monstrosities created by this image generator, and
it made me really feel calm that if I were
to actually help my friend create character images for some
of her creations, I would actually work with an artist.
(05:10):
I would hire a human artist to work with, because
then I know I would be one helping an actual
artist get work, which I think is really important and
to get what I wanted. But countless startups have launched
since late twenty twenty two, when open ai really got
the ball rolling by introducing chat GPT. Though to be clear,
(05:30):
there were already some generative AI applications available before chat GPT.
I would just say chat GPT launched everything into the stratosphere.
But here's my problem. Generative AI is just one implementation
of artificial intelligence, and it's not the only kind. AI
is actually an enormous discipline. It covers a huge amount
(05:52):
of ground like computer vision and image recognition that falls
under AI. Natural language processing is part of AI, and
obviously it has to be part of generative AI too.
If you're going to get anything that even resembles what
you were asking for, a lot of robotics falls under
the category of AI. Not all of it, but a
lot of it does. And on top of that, you
(06:13):
know the fact that we have all these different kinds
of AI and not just generative means that using the
blanket term the umbrella term for one specific implementation is
really not very accurate. But on top of that, some
companies are using AI pretty liberally to cover stuff that's
not even really artificial intelligence, like stuff like just algorithms.
(06:36):
And yes, algorithms are part of AI, they can be
part of AI, but that doesn't mean an algorithm by
itself should be described as AI. So if you've got
an algorithm that is looking at what I'm browsing, you know,
I'm looking at maybe vinyl record albums of the New
York Dolls, and then it do you have a recommendation?
Algorithm says, hey, maybe you should check out Velvet Underground.
(06:58):
That's not exactly artificial intelligence, although it is an excellent suggestion.
But because AI is so buzzy, right, it's such a
popular buzzword, there have been this ton of startups that
have begun to use AI to describe their pitch to
investors and to media. I can't tell you how many
unsolicited emails I get every single day from PR firms
(07:22):
representing clients who are trying to position their business as
the next big thing in AI, and sometimes, in fact,
I would argue frequently, they have little to no connection
to the actual discipline of artificial intelligence. On top of that,
I am also frustrated that so many businesses seem anxious
to jump into AI or else. I guess they're worried
(07:45):
they'd be left behind, but it seems to me that
many of these businesses have very little to no strategy
that's actually connected to AI. It's almost as if the
idea of AI is some sort of fix all solution
to every problem. That is going to be probably the
coda for this podcast. The motto of this is that
(08:06):
there are these buzzwords that people use, and it's almost
like a shortcut or a get out of jail free card,
where you've got this problem or challenge or goal in mind,
but you have no idea how to achieve that goal,
or overcome that challenge or solve that problem, So you
just use this kind of blanket term to stand in
(08:28):
place of an actual solution, and then you're just magically
where you need to be, and we all know that's
not really how the world works. I wish it were.
I would love to be able to use that kind
of logic to fix all sorts of things in my life,
but that's just not how it works. And you know,
you can't just open a big old box that has
the label AI on it and then business will magically
perform better. It's kind of like how I am with
(08:50):
electric guitars. So rather than practice on the electric guitar
I literally have standing right next to me. Sometimes I think,
you know, I should really buy a new guitar, as
if some how that new guitar is magically going to
make me a better player. And I can tell you
from experience that doesn't work either. And also my partner
would likely kick me out of the house if I
try and do that again. So I think the four
(09:12):
guitars I have are enough. Before we move on, we
should lump in some other AI related terms in here,
because AI, while that one alone is extremely buzzy and
people misuse it or you know, misinterpret it all the time,
there are others that fall into that same general category,
like machine learning and deep learning. They do have meaning.
(09:33):
These terms actually do mean something, so does AI for
that matter. They have meaning and they have relevance, but
they are frequently overused or misused by various tech companies
out there. And that's not good because you know, it
can set unrealistic or incorrect expectations, and then when those
expectations aren't met because the person had the incorrect interpretation
(09:54):
of what the terms actually meant, then support for research
and development in those kinds of fields can decline. And
I know that sounds kind of dramatic, but it's happened
again and again and again. It happened with virtual reality.
You know, we're seeing it possibly happen with mixed reality.
If someone's working on a research project and then they
find out that their funding has been cut because the
(10:16):
people who are in charge of the purse strings had
the wrong idea of what your work actually is all about.
And then once they find out what it is about,
they're like, oh, well, that's not what I wanted and
they cut off funding. That stinks, right, That really did
happen with VR in the nineties. You had people who
are working on important implementations of VR. I'm not talking
just like games, which I mean, I think games are important,
(10:39):
but beyond that, using VR for things like treating mental illness,
and then all the money for research kind of dried
up because people were disillusioned with what VR actually was
compared to what they thought it was. This stuff happens, Okay,
Next up, I want to talk about disrupt and disruption.
So these terms have been around for a while, and
(11:00):
it's a dramatic word. Typically, it just means that someone
has figured out a new way to do something. Sometimes
it's not even a new way. Sometimes it's just a
way that's a little bit different from how everyone else
is doing it currently. But it might be a very
old way that just fell out of favor and then
you kind of resurrect it. Now, the implication of disruption
is that this new way of doing things is going
(11:21):
to upend the industry it's in as a whole, and
that it will threaten the security of companies that refuse
to adjust to this new method and it will leave
them in the dust if they're unable to adapt. And
it's easier to understand if we just consider a couple
of examples. Amazon, for instance, disrupted retail. But how did
it do it well? It did retail online starting with
(11:43):
books and then eventually encompassing pretty much everything you can imagine.
And I would argue that Amazon really isn't that much
different from other huge retail companies in that many of
the strategies employed by Amazon are similar to ones that
were honed by companies like Walmart. It's just that Amazon
cut out the brick and mortar stores for the most
part and employed some other technologies to personalize the experience. Plus,
(12:07):
you know, buying stuff online means people don't have to
interact with other human beings, and for a not insignificant
slice of the population, that is a huge selling point.
Oh I don't need to talk to a person, I'll
just buy it online. Uber Lift and other ride haling
companies disrupted the taxi industry, which obviously has been a
real sticking point in various places around the world where
(12:28):
taxi companies have a great deal of influence. We've seen
examples of local governments cracking down on these kinds of
startups for sidestepping regulations that the taxi industry must obey,
and there have been attempts to refer to these as
ride shares, but because it's actually all about funneling money
through to the parent organization like Uber or lyft or whatever.
(12:50):
It's not really ride sharing, it's ride haling, so it
really is more like a taxi service than say, just
connecting people who happen to want to get to the
same place the same time. And there are a lot
of other examples. Of course, Airbnb is disruptive to not
only the hospitality industry but also real estate. I mean,
it's hard for folks who are just starting out to
go out and buy a house when the market caters
(13:11):
to rich people who want to add to their portfolio
of rental properties. But not everything that's being called disruptive
is actually upsetting apple carts. Sometimes the things that are
being called disruptive are just a new kind of business.
Sometimes it's describing a way of doing things that's different,
but it's not necessarily advantageous compared to how the industry
(13:33):
as a whole is doing whatever the thing is. And
a lot of leaders really hate the term disruptive because
it can distract folks into pursuing disruption at the expense
of actually making a business model that works. If you're
banking on everything causing disruption in an established market and
you're not actually spending effort making sure that your approach
even makes sense. You're just trying to watch the world burn.
(13:56):
Related to disrupt is the term game changer. That phrase
implies that the business model forces a change on an
entire industry, it changes the game. That very rarely happens. Instead,
we often hear game changer applied to businesses that are
just new, even ones that aren't doing anything particularly that
(14:17):
differently from their competitors or performing better than their competitors.
Sometimes they're performing worse. That's hardly changing the game. Okay,
we've got tons of other buzzwords to get through. Before
we do that, let's take a quick break to thank
our sponsors. We're back. Time to talk about some more
(14:43):
buzzwords that get a lot of hate on these lists.
This next one is a huge one. It sometimes ranks
is number one depending upon the year, and that is
digital transformation that popped up on multiple most hated buzzwords
and tech lists. John Moore of tech Target first this
definition of digital transformation. He says, it is quote the
(15:05):
incorporation of computer based technologies into an organization's products, processes,
and strategies. Organizations undertake digital transformation to better engage and
serve their workforce and customers and thus improve their ability
to compete end quote. So it's kind of like modernizing really,
(15:26):
is what I would call it. You know, you're trying
to figure out how can we take these various legacy
systems and processes and bring them into the digital age,
potentially making things easier to manage and monitor and measure
and all those sorts of things. Cindy Jondon of IFS,
which is a cloud computing company, says, quote, it's really
(15:48):
a seismic shift forcing organizations to better enable their teams
and improve asset usage and customer experiences end quote. To me,
that's teetering pretty darn close to being too vain to
be really useful. But at the same time, you could
argue that each organization is going to have its own
specific set of requirements and challenges, and so therefore it's
(16:09):
impossible to get specific, right because if you get specific,
then you're leaving out lots of other use cases, so
you have to be really general. But yeah, that particular
description to me borders on not being very useful. Now,
as pointed out on CMC Globals site, and issue with
the concept of digital transformation is that there's a tendency
(16:31):
to treat it again as a magical panacea similar to AI,
right that by somehow just porting processes over into a
computerized system, maybe even one that's networked, based on the cloud,
whatever it may be, you have somehow transformed the business inherently,
even though it's the exact same processes and everything, it's
just now it's done in a different way. Business strategy
(16:53):
is still absolutely important, and without business strategy, shifting how
you do things from one model to another doesn't actually
address fundamental issues. Again, it's like you're slapping a band
aid on something and you don't even understand it. It's
like if someone had a cold and you put a
band aid on their arm doesn't really address the problem.
There's no denying that modernizing systems so that they're more
(17:15):
easily accessible and adaptable is really important. But as Mark
Bilger of One Call puts it, quote digital transformations do
not magically transform the business. A fool with a tool
is still a fool, end quote. Kind of dig that.
There are a lot of companies out there that do
consulting work on digital transformation. I'm sure some of them
(17:36):
are quite good at it, but in my experienced consultants
are the absolute worst when it comes to leaning on
buzzwords in jargon to obfuscate what they mean. And I
feel like I can say that with some authority because
in my previous professional life, before I ever worked for iHeart,
before I work for Discovery Communications, before I work for
house stuffworks dot com, I spent more than seven years
(17:58):
working for management consultants. And I've read a lot of
proposals and a lot of reports, y'all, And one thing
I walked away with is that consultants just love to
use language that ultimately doesn't mean very much but sounds good.
Another big buzzword that makes these lists, and it's been
around for quite some time at this point, is the cloud. Now,
(18:19):
there's a meme that goes around that is one hundred
percent accurate that says there is no cloud, It's just
somebody else's computer. That's true. That's the basic truth of
what the cloud is. Cloud computing, cloud storage, cloud development,
whatever cloud service you're talking about. Ultimately, these all describe
a situation in which the thing you are using is
(18:40):
a computer system that's provided by a third party, and
that's it. That's the magic of the cloud. So It
may be that it's an operating environment. It may be
that it's you know again, storage. It could be any
of those things. But really it just means that these
these services are living on computers that are some else. Now,
(19:00):
cloud solutions free up businesses so that they don't have
to host their own services on premises or in tech speak,
on prem. I cannot tell you how much I hate
on prem not the concept but the actual use of that,
as if on prem is somehow saving you a huge
amount of time as opposed to saying on premises. In
(19:21):
my humble opinion, on prem is just a way to
create a code language that in small ways excludes outsiders
from your group. It's kind of akin to the Little
Rascals having the he Man Woman Haters Club, though I
really guess only a fraction of y'all probably know who
the little Rascals are. I'm old, but anyway, my commentary
aside the issue many take with cloud terminology is that
(19:44):
people will frequently use the phrase, similar to what we
saw with AI and digital transformation, that it's some kind
of cure all for any business challenge. There are definitely
really good reasons to use cloud services, right like you
might not be able to scale your services to your
customers if it became really popular. Right, if you host
(20:05):
everything yourself and everything's running on servers that are in
your own office space or garage, whatever it may be,
and you suddenly get really popular, you could end up
having your service completely overwhelmed and now you can't provide
services to anybody. And this is also kind of a
good problem to have. It means that your services are
resonating with customers, but you don't want the experience for
(20:27):
them to be to log in and find out they
can't access the thing that they're paying for. That's bad.
So leaning on a large, established cloud provider could be
the solution. It might be that, oh, well, we can
scale just by purchasing more compute power or more storage
from this provider. But just poorting stuff from your own
(20:48):
systems to the cloud doesn't automatically make them work better
or reach more customers. It's not like the company providing
the cloud services is going to be doing your marketing
for you or anything, because they've already got their customer.
Their customer is you. It's your job to go out
and get your own customers. But yeah, cloud computing is
often used as sort of this hand wavy way of saying,
(21:09):
don't worry about these problems, we got it covered, when
in fact, the cloud does not magically solve stuff on
its own. Again, this is a real issue with a
lot of these buzzwords. If I'm being honest, it's really
it's not the word's fault necessarily, it's that folks are lazy.
People are lazy and they don't want to have to
really tackle and define the real challenging business or tech
(21:31):
issues that they're facing. That's hard. This is very hard
to actually identify and then solve these tough business problems.
It's really hard work. So it's way easier to just
use a phrase or a term and to take a shortcut,
especially if you're an executive, and then you foist the
actual problem onto your underlings and it's their job to
(21:53):
actually figure out, Okay, well, how do we do the
thing that our boss wants us to do when all
our boss says is cloud compute or digital transformation. To me,
this is kind of like the underpants gnomes in South Park,
You know the underpants domes. They say phase one is
collect underpants, phase two is something, and phase three is
profit that's what a lot of these buzzwords are. You know,
(22:14):
the buzzwords are phase one, Phase two is completely undefined,
and then phase three is somehow huge success. And I'm
sad to report again it usually does not work out
that way. All right, So what's next? Well, I guess,
I mean, I didn't want to have to do this
because I really don't like covering these kinds of things,
but it's time to tackle blockchain and the related buzz
(22:35):
terms around that. So blockchain is a thing, right, I'm
not saying that blockchain doesn't mean anything. It absolutely does
mean something. It's mostly a thing that people associate with
cryptocurrencies because that's where it's seen the most use and
I would argue the most success. But blockchain evangelists proclaim
that blockchain is going to underpin the entirety of the
(22:57):
Web of the future. This will play into a another
buzz term we'll talk about shortly, web three. Now, these
evangelists aren't always super good at articulating how blockchain will
actually underpin the web of the future, just somehow that
it will, and often a lot of details get glossed
over in the process. I mean, blockchain has a lot
(23:18):
of challenges facing it too, Like a lot of those
systems are very slow, they're inefficient, some of them are
extremely thirsty for electricity if it's based on a proof
of work approach to blockchain. So there are a lot
of issues that evangelists usually don't directly address, and they
have pretty glib answers if you start asking follow up questions.
(23:41):
But what does blockchain actually mean? Well, basically, a blockchain
is a record of transactions. Typically we're talking about a
decentralized ledger, meaning this ledger does not exist in any
one given computer, it is distributed across lots of different computers,
and this ledger is a record of all these transactions.
(24:02):
And not only is it a record, it's viewable by
a collection of stakeholders. So in some cases those stakeholders
could be everyone who is connected to and is using
the system. So in other words, it's as public as
it gets, right, as long as you are part of
the system, you can actually view the ledger. But in
other cases, we could be talking about a closed blockchain
(24:23):
and which only a select number of parties have access
to that ledger, even if the blockchain itself is a
foundation for a service that lots of other people are using.
So you might have tons of people using, say a
specific cryptocurrency, but only a small collection of stakeholders are
able to actually view the ledger itself. That is problem
number one. Actually, often I hear or read about projects
(24:46):
that are pitched to be built on top of a blockchain,
and the implication is that this makes the system inherently transparent.
It doesn't. For example, there was Facebook, which is of
course now called Meta, and Facebook's attempt to ch a
cryptocurrency initially called Libra, later it was called DM. Actually
technically Libra itself was I think the second name for it,
(25:07):
but Libra and then DIM. The blockchain serving as the
foundation for this particular cryptocurrency was going to be the
domain of a consortium of companies that initially was called
the Libra Association, later became the DM Association. So instead
of a community of users all having access to this
distributed ledger of transactions, it would be this consortium. But
(25:29):
that ultimately did not work out. The whole project got
bogged down, a ton of companies that initially had signed
on to be part of the consortium bailed on it. Ultimately,
the consortium sold off what few assets it still had
to a bank called Silvergate Capital for a couple hundred
million dollars. At least that was the belief. The money
amount was never made public, but then Silvergate subsequently shut
(25:51):
down the following year. Because this stuff is hard, y'all.
I mean, if Facebook can't do it, it's really hard.
We'll come back to that when we talk about the metaverse. Anyway,
the selling point for blockchain technology is that the record
of transactions is both transparent and it is reliable because
each block of transactions is cryptographically linked to all the
(26:11):
previous transactions in that ledger, and we'll be linked to
all subsequent transactions in that ledger. And this means that
no one can tamper with the records of previous transactions.
If you went back and tried to change the record
further back on the list, like let's say it's three
blocks back, well, that would actually make changes to the
(26:33):
next two blocks. It would be impossible to hide. So
there's no bacxies. Every transaction is permanent. You know, you
could do a new transaction with the exact same assets,
right Like if you had purchased something and then you
wanted to turn around and sell it you could do that,
but you couldn't purchase something and then go back and
erase the record of you purchasing it so that you
(26:54):
magically get your cryptocurrency back. You can't reverse an earlier
transaction that way. So this leads some to say, aha,
we can use blockchain to serve as the bedrock for
all online transactions. I mean, you could do it to
keep record of like buying a house. You know, you
enter that transaction into a blockchain that shows proof of
this transition of ownership of the property. No one else
(27:16):
can claim to own your property. You've got the record
right there, and it is unalterable and irreversible. So the
blockchain will show that the transaction happened and will serve
as proof that ownership has changed hands. Moreover, it can
serve as a record for digital transactions, which are a
lot more whibly wobbly than stuff that you can buy
and sell an actual meat space. So, for example, let's
(27:37):
say I wanted to buy a clip of music. Maybe
I even want a smart contract that gives me the
license to use that music clip in some other work,
such as an episode of a podcast. Well, you could
set that up on a blockchain ecosystem to show proof
of this transaction, and that could stand as the record
indicating that I, as a customer, have legally purchased the
(27:57):
license to use a clip of someone else's music in
my work. Now that's just one hypothetical example. This does
tie into n fts or non fungible tokens. But there
was obviously a huge problem with NFTs as they rolled out, Namely,
they became a target for insane and unsustainable speculation. So
folks were buying up NFTs with the expectation that these
(28:18):
digital assets were going to escalate in value, and a
lot of companies got in on the NFT craze. They
saw it as a way to essentially print money, or
they were afraid of being left behind, and ultimately the
NFT bubble popped and laid waste to the entire landscape,
and it also did an enormous amount of pr damage
to the NFT concept as a whole. So even folks
(28:39):
who were coming up with undeniably interesting ideas for NFTs
found themselves scrambling for interest and support because the speculative
market had burned so many people. Okay, we're coming up
on the last third of our podcast and speaking of thirds,
we'll be talking about Web three next, but first let's
take another quick break to thank our sponsors. All right,
(29:11):
we're back and we're going to talk about web three now.
A lot of the buzzwords we've talked about so far
have an actual meaning, right, They do have meaning to them,
but often there's this issue of people misinterpreting or misusing
the terminology, misconstruing something, and then the meaning of those
(29:31):
other terms gets a little fuzzy. Web three is not
like that, though, because it doesn't really have a definition.
It's kind of like the term metaverse, which we will
talk about in a second. In fact, I would argue
web three and metaverse are very similar in that regard.
They are both words used by people to make some
pretty vague statements about a kind of hazy future of
(29:53):
online interaction and commerce and society. But once you start
to dive down into it, you start to discover that
there actually are a lot of different takes on what
these things are ultimately going to be, and so it
doesn't seem like anyone's really on the same page, Like
there are a lot of similarities, but there are a
lot of differences too, and this ultimately means there's not
(30:15):
a really meaningful way to talk about these kinds of things.
But you still have companies jumping on board in an
attempt to establish a presence in an undefined field or
else lose some sort of unknowable advantage. So generally speaking,
most versions of Web three share certain qualities. One of
the big ones is decentralization. So a big criticism of
(30:37):
the current web is that power and influence gravitates toward
a few massive players in the space. We're talking big
companies like Amazon and Google, for example, and there's no
denying it, Like, there are certain companies that have a
stranglehold on the massive amounts of data that pass over
(30:57):
the Web, And so the thought is, wouldn't it be
better if we democratize that power somewhat? We took it
so that the next version of the Web is not
entrusted into the hands of these corporate mega giants, but
rather to the users. You know, that's what evangelists like
to say, put the power in the hands of the users,
which is kind of like tron. Critics of Web three
(31:20):
say that most of the Web three implementation ideas would
really just create different power brokers for the Web. It
wouldn't be the big companies that we talk about, the
big tech companies, but it would go into the hands
of a wealthy subculture that would be able to afford
to act as the cornerstones of this new web. So
really it doesn't democratize who owns the web. It just
(31:41):
designates different stakeholders, the folks in charge of overseeing the
various systems that Web three is actually built upon, which
usually involves some kind of blockchain technology and token economy.
Now I don't mean a token economy. I mean an
economy based upon the minting, buying, selling, and trading of
digital tokens. And we heard a lot of buzz about
Web three just a couple of years ago. And to
(32:03):
be clear, there are still companies that are working toward
making something along the lines of a Web three implementation happen.
But the excitement around this has fizzled out quite a bit.
And I honestly I think that artificial intelligence has managed
to drink an awful lot of tech milkshakes. So you
can also look at the metaverse as an example of this,
(32:25):
where some of that excitement has been ported over for AI.
In fact, according to Gopal Solanki, who wrote a piece
on Medium that's titled is Web three dead already? He
said investment in Web three companies has fallen by more
than seventy five percent in twenty twenty three compared to
the levels it had in twenty twenty one. He went
(32:45):
on to say, we cannot say that Web three is dead,
but it has surely failed to deliver the promises it made.
Each innovative idea presented in the form of renovated web
version has turned into complete dust on unless it has
something to do with the native cryptocurrency token. All the
developments and projects introduced in the Web three hype are
(33:07):
majorly underperforming. That seems to sum it up to me.
I can't disagree with that, and not to say that
something called Web three won't come down the line, but
in the meantime, that term is largely without meaning, and
it's mostly used by people who are scrambling for funding
for something that's unproven and potentially no better than what
(33:30):
we already have. In fact, potentially it could be worse.
Things like transmission speeds and stuff could be drastically affected
because again, blockchain transactions are not the most efficient. So
if you build everything based on blockchain transactions like online
commerce is completely based on blockchain. It could mean that
it's just overwhelmed that it's far too slow to deal
(33:54):
with that level of responsibility. All right, Well, then let's
tackle metaverse and mixed reality, more stuff that went through
the hype cycle and recently has struggled to remain relevant.
Starting off with the metaverse, we're talking about a concept that, again,
like Web three, does not have a firm definition. There
are a distinct lack of details. Generally speaking, most definitions,
(34:17):
if you can call them, that, imply a persistent virtual
world in which you can explore and socialize and shop
and create and consume, kind of like a computer generated
alternate reality to the reality we experience if we step
outside our houses. Some versions of the metaverse tap into
similar stuff that we hear about in Web three, like
(34:40):
cryptocurrencies and blockchain. Other versions of the metaverse focus more
on the virtual reality aspect and things like creating your
own avatar and being able to maneuver around these virtual environments.
Some versions of the metaverse describe a huge, interconnected series
of virtual worlds kind of hosted by different intit so
(35:00):
there might be one that's owned and operated by Meta
and another one owned and operated by Amazon, and maybe
they're interlinked together so you can pass through from one
to the other, kind of like how the web itself
is a big interconnected series of web pages, but instead
you're talking about a virtual world with like three dimensional
virtual space, but like web three. A lot of the
(35:22):
enthusiasm and excitement around the metaverse has kind of gone
cup put in recent years. There was a flurry of
excitement about the metaverse idea for a while, and you
had people and companies that were rushing to establish a
presence on various platforms, claiming that these platforms would become
pillars of the upcoming metaverse. But you don't hear about
(35:42):
that as frequently these days. It kind of blows my
mind that virtual real estate sold for real money, sometimes
a significant amount of real money, even before any such
platform had established itself, as you know, a real thing
that people wanted to go and spend time at. It's
kind of like this wild land rush, except land in
(36:03):
the real world is a finite resource, and the only
thing stopping yet another company from launching a virtual real
estate company is computational hardware. Scarcity is not really a
thing in the digital space, which again brings us back
to the challenges of digital assets and transactions anyway. Obviously,
there are still companies that are working on creating a metaverse,
(36:24):
but the question I have is how many folks are
actually itching for a metaverse. I wondered that from the
very beginning. I definitely wonder it. Now. Meta has spent
billions with a b of dollars on such efforts. It
continues to do this, much to the chagrin of investors,
and I am still not convinced that those efforts will
have a good return on investment. Maybe we'll get some
(36:46):
virtual environments out of it, and some of them might
even be really good and compelling experiences, but I don't
know that that's going to be enough to get the
results needed to make those billions of dollars a sound investment.
I don't know if it's going to make that, you know,
the metaverse the future of online interaction. But then again,
I'm not a genius anyway. There are tons of barriers
(37:08):
that the metaverse will have to overcome in order to
become a real thing. And real thing you can put
in air quotes. I guess, assuming that you know it
does involve virtual reality. One of the hurdles for the
metaverse is the cost to the consumer, because VR headsets
aren't cheap. Now, there are some headsets that are significantly
less expensive than earlier models, so they aren't necessarily as
(37:30):
expensive as they used to be, but they're still not cheap.
And computers are really versatile technologies, right, You can do
a lot of stuff on a computer. Now, you could
arguably do most of that same stuff, if not all
of it, while wearing VR gear as well, But that
requires a lot of work to design a really good
user interface so that the person who's wearing the VR
(37:51):
gear can do whatever it is they want to do
in a way that makes sense and feels natural. But
if you can already do pretty much all of that
stuff on a computer, you know, with the exception of
being in an immersive virtual environment, I'm not sure the
sales pitch is good enough to get people to buy in. Also,
this whole concept of an online world that is persistent
(38:11):
and virtual and even three dimensional isn't new. Folks have
been talking about that for years. Heck, you watch old
Hollywood films that represent the web, and it almost always
has someone seeing at a computer, and it looks like
they're playing some sort of weird first person shooter navigating
through stuff, because that looks way more exciting than just
staring at a page full of text and hyperlinks. Right,
(38:34):
But you know, navigating through a virtual space in order
to get to a destination has never made much sense
to me. Like, instead of having websites, having you know,
maybe like a virtual mall of stores and you have
to wander around in order to go to places, that
just doesn't make sense. Clicking on a link is super
fast and efficient, and sure you could build that kind
(38:54):
of capability into the metaverse, you know, maybe you make
it a voice command. But is the experience of just
teleporting from one virtual spot to another, perhaps, you know,
just to do some shopping, or maybe even just check
the news. Does that really sound like an experience most
people want to have, because I think it would be
pretty disorienting and distracting and inefficient. You could do it
so much faster just using a computer or a smartphone.
(39:16):
But really, whether you think like I do and you
find the whole metaverse concept puzzling, or if you think
it's a great idea, there's no getting around that. Tons
of folks and companies. We're using metaverse as shorthand for
this is the future. Nearly every press release or announcement
I saw relating to the metaverse said very little apart
from we're forward thinking and we're super cool, without you know,
(39:39):
doing anything to back up those claims. Just as cloud
computing and digital transformation can be used as buzzy shortcuts
to avoid addressing real challenges, I feel like the metaverse
and web three come across as more or less meaningless
terms used to proclaim relevance. You know, they might not
be anything today, but maybe tomorrow. Right, you'll see and
you'll see it from us, because we're hip and we're
(40:01):
with it. Okay, I'm really old, So maybe I'm just
way too cynical. Maybe it's brought on by the fact
that a lot of early attempts at showcasing ideas that
are at least intended to be incorporated into the metaverse
have been a bit disappointing. This brings me to mixed
reality now, y'all. I love me some mixed reality. I'm
(40:21):
not as big on VR these days. I acknowledge that
VR is the far more successful end of the mixed
reality spectrum. VR at least has established use cases in
the form of gaming. My problem is physiological because as
I get older, I get more prone to motion sickness,
which stinks. It's not the technology's fault necessarily, unless latency
(40:42):
is really bad, in which case it is the technology's fault.
But you know, I used to be the guy who
would ride a roller coaster two dozen times in a
day and think nothing of it. Now, if I ride
two different roller coasters in a row, I have to
lie down for forty minutes, So that's on me. But
VR has a place at the table, right It's an
established technology, and there are some great VR games and
(41:04):
experiences out there. It's still not necessarily a large enough
library of experiences to get a critical mass of users
on board, but the audience for VR tends to be
fairly enthusiastic or at least curious to try VR stuff.
I do know a few people who have VR setups
that have gone untouched for you know, long enough for
them to gather dust, So I don't know how common
(41:25):
that is. I'm sure there are people who use it
every day, you know. I've got a friend who uses
VR to do exercise with beat saber and that's you know,
she's not alone. Lots of people do that. It's on
the augmented reality side where I am actually the most interested.
But I simultaneously have to admit that not nearly enough
has been done in the AR space to make it
(41:46):
really useful outside of some very specific implementations. And I
think it's easy to imagine how AR could be useful,
Like if you can overlay digital information on your view
of the real world around you. There are countless ways
to make that really useful, everything from just entertaining to
genuinely answering questions or letting you do things more efficiently.
(42:07):
But while the technology has potential, we haven't really seen
that potential realized, and it's been a challenge so difficult
that even Apple appears to be struggling with it. Apple
launched the Vision Pro earlier this year. The year in
question is twenty twenty four for many of y'all listening
from the future. An initially word was that despite the
incredibly hefty price tag of three thousand, five hundred dollars
(42:29):
for the base model of this headset, the company was
actually going to sell out of its initial production run. However,
it's just a few months later and the story has changed.
An Apple analyst named Ming chi Quo posted that the
company was cutting orders by nearly half for the rest
of twenty twenty four, downgrading the expected unit sales that
(42:50):
initially were projected to be seven hundred to eight hundred
thousand units down to four hundred thousand to four hundred
and fifty thousand, which is a big old' oof because
demand dropped very quickly. Wes Davis of The Verge posted
an article recently that said he was finding listings on
eBay in which the headsets were selling for far below
market price, and Davis says it stings to know that
(43:11):
he could have waited and purchased a Vision Pro for
much less than what he actually paid for it when
it first became available. But really, I would argue that's
just the tip of the iceberg for consumer pain when
it comes to mixed reality, because I think the real
problem is that, facing a lack of a really big
user base, developers don't have a lot of reason to
make applications for AR hardware, because why would you spend
(43:35):
your time and your energy and your skills making something
that hardly anyone is going to get to use? But
if developers don't embrace the hardware, then consumers don't really
have an incentive to shell out the considerable amount of
money it costs to buy one of these headsets. It's
a catch twenty two issue, right because I don't want
a vision pro because I feel there aren't enough applications
(43:56):
for it. But no one's going to build applications for
the vision proh because people like me don't want to
purchase one. And then it's very possible that Apple will
either have to scale the tech way back so it
can introduce a significantly less expensive headset, which presumably would
have far fewer features and make it less attractive, or
just back away from the effort entirely and say this
(44:19):
one is a loss. My whole point is that if Apple,
with its famous reality distortion field, can't get mixed reality
to work in the market, it might just be too
early for that technology to take hold. Now, maybe someday
it'll be a big success, but it's going through its
own rough time, kind of similar to how VR really
struggled after a similar issue in the nineteen nineties after
(44:44):
that hype cycle kind of deflated. And this brings me
to a conclusion as well as a general warning that
I think it's really good to remember. If someone is
pushing very hard to sell you an idea, whether that
idea is AI, it's web three, a blockchain, or the
metaverse or mixed reality or anything like that, it often
(45:05):
indicates that the person talking to you is heavily invested
in that particular technology, and in order for their investment
to pay off, they need to get other folks to
buy into it. Now, I don't mean to say that
all of these ideas are ultimately nothing more than a
pyramid scheme, but they sure do operate that way in
the early days, and you don't get paid out unless
(45:27):
folks lower down the chain buy in. So buyer beware
is what I'm saying. Use critical thinking, make sure you
ask questions and make sure that the answers are satisfying
and that they mean something, and it's not just filled
with buzzwords and jargon. And for the leaders out there,
really think about different ways you can communicate your ideas
that aren't necessarily reliant on buzzwords, that actually do define
(45:51):
challenges and problems and solutions, because otherwise it starts to
sound like you're using language to cover the possibility that
you don't know what you're doing, and that's not a
good look at all. Doesn't serve anyone well in the
long run. All Right, that's it. Like I said, there
are tons of other buzzwords that we could include here,
(46:13):
and maybe I'll do another episode in the future with
more of these, but I thought this was a good
roundup for an episode like this. I hope you are
all well, and I'll talk to you again really soon.
Tech Stuff is an iHeartRadio production. For more podcasts from iHeartRadio,
(46:37):
visit the iHeartRadio app, Apple Podcasts, or wherever you listen
to your favorite shows.
TechStuff News
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Jonathan Strickland
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