July 7, 2025 • 18 mins
In this episode of Hashtag Trending, host Jim Love discusses Staples Canada's new trade-in program aimed at reducing e-waste while easing financial burdens for back-to-school shoppers. In the AI domain, TNG Technology Consulting has unveiled a groundbreaking model substantially faster and more cost-effective than its predecessors. An international research team brings Quantum computing closer to practical use with the launch of QNodeOS, the world's first operating system for quantum computers. The episode also examines conflicting viewpoints on the potential job market impact of AI, with statements from industry leaders Sam Altman and Dario Amodei highlighting a looming white-collar job crisis.
00:00 Introduction and Overview
00:24 Staples Canada's E-Waste Solution
03:22 German AI Breakthrough: TNG's Deep Seek TNGR
08:09 Quantum Computing's First Operating System
12:26 The AI Job Crisis: Perspectives and Predictions
18:34 Conclusion and Sign-Off
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
(00:01):
Staples Canada tackles themillion ton E-waste crisis.
A German model is 200% faster than deepseek scientists create the first quantum
operating system and the AI job crisis.
Who are you gonna believe,Sam Altman or your lying eyes?
Welcome to hashtag Trending.
(00:21):
I'm your host, Jim Love.
Let's get into it.
I can't believe I'm saying back toschool already, but as retailers
prepare for back to school shopping,staples Canada has launched a solution
that tackles two problems at once.
The financial strain of buyingnew tech and Canada's mounting
electronic waste crisis.
(00:42):
The new Staples Trade-in program letsCanadians exchange old smartphones,
laptops, and tablets for instantgift cards and for consumers who
might be a little freaked outabout the economic uncertainty and
grappling with increasing costs.
The idea of being able to trade inolder electronics has an appeal, but
(01:03):
there's an added benefit grapplingwith nearly 1 million tons of annual
E-waste created in Canada alone.
New research from the Universityof Waterloo reveals that Canada's
electronic waste has more thantripled in the last two decades.
Jumping from 8.3 kilograms per personin 2000 to 25.3 kilograms in 2020.
(01:28):
By 2030, Canadians are expectedto generate 1.2 million tons of
e-waste annually, equivalent tofilling the CN Tower 110 times.
Rachel Huckle, CEO of Staples, Canadasays The company is committed to making
it easier for consumers to access thelatest technology in a smarter and more
(01:52):
sustainable way, The program addresseswhat researchers call Canada's Forgotten
Repair Culture, where functional devicesare discarded simply for newer models.
Customers answer a few questionsonline about their device's condition,
and receive an immediate quote.
Once accepted, they get a Staples E-giftcard redeemable immediately at any
(02:15):
one of Canada's 298 Staples locations.
The old devices can either be droppedoff at their local store or shipped
directly to Allstate Staples partnerin the program using a prepaid label.
Allstate Protection Plans, powerswhat the company calls a circular
economy enablement, handling everythingfrom device valuation to certified
(02:39):
refurbishment and responsible recycling.
That's a win-win for customers',wallets, and the planet.
Staples joins a small group of retailersthat are tackling E-Waste head on
However, few major retailers haveintegrated trade-in value with immediate
purchasing power the way Staples have.
(02:59):
The program launches as back to schoolspending peaks when families are most
likely to upgrade devices for students.
It makes old tech immediatelyconvertible to purchasing power at
a time when families need it most,and as a person with a basement
full of tech too good to throw out,but with no place to see it reused.
(03:19):
This is a good idea.
The AI world is buzzingafter a 24-year-old German
consulting firm just dropped.
What developers are calling a holy sh Soa holy smokes, uh, level of innovation.
If you remember the sensation causedby the launch of Chinese AI deep
seek, which provided an open sourceAI with full weights, in essence,
(03:43):
pre-trained, that ran on what?
Compared to ChatGPT or otherswas a tiny hardware profile.
Developers claim that while training costsof ChatGPT and similar models could be
between 70 and a hundred million dollars.
They'd done all the training for under$6 million, but you don't need to worry
(04:03):
about that even because they shippedthe model with its weightings or the
training intact and the processingcosts of this model were a small
fraction of the larger frontier models,
It was and remains a bit of a miracle.
The US embargo restricted theChinese on how much and what
kind of GPUs they could buy.
(04:25):
Well, they made a virtue outta the problemand delivered what might be the most
efficient and cheapest frontier model.
And as the commercialsays, it's open source.
You can't save more money than free.
So where does anyone go from there?
Well, TNG Technology Consulting, aMunich based firm has released a new
(04:47):
version of Deep Seek TNGR one T twoChimera, and it's reportedly wait
for it 200% faster than deep seeks.
Latest.
R 1 5 2 8 while maintaining90% of its intelligence.
And did I mention they'regiving it away for free?
(05:10):
While OpenAI, Google and Anthropic Battlefor billions in funding TNG Technology
Consulting, a Munich based firm with800 employees just demonstrated that
breakthrough AI innovation doesn'trequire Silicon Valley budgets.
The secret weapon.
A technique called Assembly of Experts.
(05:31):
It merges the best part of multiple AImodels without expensive retraining.
There's a lot of hype in thisbusiness, but the excitement appears
at least, somewhat justified.
R one T two not only is free, not onlyis fast, but it achieves the speed boost
by generating responses using just 40% ofthe tokens required by its predecessors.
(05:56):
And tokens are the essential unitof processing, meaning dramatically
lower costs and faster responses.
TNGs breakthrough comes from thinkingdifferently about AI development.
Instead of training massive modelsfrom scratch, their assembly of experts
methods selectively combines thereasoning power of DeepSeek, R 1 0 5 2 8.
(06:19):
The structured thinking ofthe original R one and the
efficiency of their V 3 0 3 2 4.
The result is a model engineered tomaintain high reasoning capability
while significantly reducing inferencecost, inference being the process
that happens after the prompt.
(06:40):
Some have called it.
Automotive engineering applied to ai.
Rather than building a completely newengine, they've created a hybrid that
gets the performance of a V eight withthe efficiency of a four cylinder.
Now, this isn't justabout bragging rights.
The model maintains elite.
Performance on advanced reasoning tests.
Scoring between 90 and 92% of R 1 0 52 eight's results on mathematical and
(07:06):
graduate level problems while slashingoperational costs for enterprises.
This translates into runninga sophisticated AI application
at a fraction of the expense.
The timing is particularly strikingas major tech companies are announcing
massive AI infrastructure investments.
(07:26):
Microsoft is planning $80 billion inAI spending for 2025, while Amazon
is committing similar amounts.
meanwhile, TNG achieved thisbreakthrough using existing
models and clever engineering.
TNG is releasing R one T two underan MIT license, meaning any company
can use, Amodeify and deploy itcommercially without licensing fees.
(07:52):
The decision puts pressureon big tech firms charging
premium rates for AI access.
Why pay thousands monthly for APIcalls when you can run comparable
intelligence on your own infrastructure?
over to you Silicon Valley,
and if you've been around it longenough, you know that computers made
(08:13):
their way into common business usagewhen they had operating systems
that provided much needed interfacesbetween machine and programs.
It happened with mainframe computers,it happened with mini or departmental
computers, and most of us.
Of a certain age.
Remember MSDOS, the operating systemthat Bill Gates and Company developed
(08:33):
that powered the PC revolution?
Well, something similar hashappened for Quantum Computers.
An international research teamhas announced that they built
the brain for quantum machines asthey unveiled QNodeOS the world's
first operating system designedspecifically for Quantum computers.
(08:55):
The breakthrough published inNature could finally bridge the gap.
Between quantum computing's,theoretical promise and practical
applications enabling different typesof quantum computers to communicate
seamlessly for the first time.
Until now, quantum computers havebeen like brilliant, but isolated
(09:16):
scientists each speaking a differentlanguage and unable to collaborate.
QNodeOS solves this fundamental problemby creating a universal translator that
allows diverse quantum technologies.
From diamond based systems to trapped ionprocessors to work together in networks.
(09:38):
QNodeOS operates through twointegrated processing units
that work like a tag team.
There's the classical networkprocessing unit, and that handles
traditional computing tasks and programexecution while the Quantum Network
processing unit manages the exotic.
Quantum operations likeentanglement and superposition.
(10:00):
Together, they control quantumdevices through a unified interface.
The key innovation is what they'recalling the Q driver, a sophisticated
translator that converts universalcommands into specific instructions
for each type of Quantum hardware.
Think of it as creating a commonlanguage that lets Quantum computers
(10:21):
built with completely differenttechnologies, understand each other.
And
The researchers demonstrated QNodeOSScapabilities by connecting it to two
fundamentally different quantum systems.
One based on nitrogen vacancy centers inDiamond and another using trapped ions.
(10:41):
These systems work as differentlyas a Formula One race car and a
submarine, and yet QNodeOS enabledthem to coordinate seamlessly.
This breakthrough addresses a criticallimitation that's kept quantum computing
largely confined to research labs.
Previous quantum systems requiredphysicists to write custom code for
(11:03):
each specific experimental setup, likehaving to rewire your computer every time
you wanted to run a different program.
QNodeOS changes this by enabling highlevel programming, just like Windows
or Android do for classical computers.
Developers can now focus on creatingapplications rather than wrestling
with hardware complexities.
(11:24):
The Quantum Internet Allianceplans to deploy QNodeOS on their
Quantum Network Explorer providingresearchers worldwide access to
experiment with quantum networking.
This could accelerate development ofapplications we can barely imagine today.
From ultra secure communicationsto distributed quantum computing
that could solve problems currentlyimpossible for any classical computer.
(11:49):
Now there are still challenges.
The researchers are working to integrateprocessing units onto a single board
to eliminate a millisecond delaythat currently limits performance.
They're also developing long distanceprotocols and error correction methods
essential for practical quantum networks.
So we've all wondered when quantumcomputing might be able to solve
(12:09):
real world problems by solving theinteroperability problem, researchers
have created the foundation fora future quantum internet that
could revolutionize cryptography,chemistry, optimization, and maybe
even stuff we haven't yet discovered.
There will be areas where some jobsgo away, or maybe there'll be some
(12:30):
whole categories of jobs that go away.
That's OpenAI's, CEO, Sam Altmanadmitting the obvious in a recent podcast.
But then when asked if he agreed withAnthropic, CEO, Dario Amodei's, warning
that 50% of entry level white collarjobs could disappear within five years.
(12:51):
Altman said he disagreed.
His Chief Operating Officer, BradLightcap, was even more dismissive.
Claiming OpenAI has no evidence thatcompanies are wholesale replacing entry
level jobs with ai, and they talk to a lotof companies according to Brad, really.
Obviously he doesn't listen to thispodcast, but really does he actually
(13:14):
listen to the news this week?
Amazon's CEO Andy Jassy told his1.5 million employees in a memo.
We need fewer people doing some of thejobs that are being done today and more
people doing other types of jobs, but.
That's a little sugar coating.
He was brutally honest.
In the next few years, we expect thatthis will reduce our total corporate
(13:38):
workforce as we get efficiency gains fromusing AI extensively across the company.
Amazon has already cut27,000 jobs since 2022.
but Jassy isn't alone.
Microsoft has laid off over 15,000employees in 2025 alone, including their
(13:59):
director of AI apparently to free up $80billion for AI infrastructure investments.
But think about that.
The company that created a way to takeChatGPT to market is cutting people
to pay for the very technology thatmight replace them, and CEO Satya
Nadella is saying that about 30% oftheir code is being generated by AI
(14:25):
If you go through a list of othermajor CEOs, you'll hear similar
stories from Salesforce saying thatabout 50% of their work could be
done by AI to social media's Meta.
It's the same story Which brings us tothe other guy, Anthropic, CEO, Dario
Amodei, who delivered perhaps the starkestwarning, yet telling Axios that AI
could eliminate half of all entry levelwhite collar jobs within five years.
(14:50):
A move he said could cause unemploymentto spike to between 10 and 20%.
His message to lawmakers, most of themare unaware that this is about to happen.
It sounds crazy andpeople don't believe it.
Now you can claim a Amodei is mistaken.
(15:11):
You can claim that he's wrong, eventhough his company is on the leading
edge of delivering some of the work,replacing agents with a variety
of partners, and he admits he'snothing to gain from this prediction.
Actually, he probably has a lotto lose if there's a backlash
against AI because of what he said.
(15:33):
that brings us back to OpenAI's.
Sam Altman, is he reallytelling the whole truth?
Some claim he's changed his storyfrom time to time When Senator Gary
Peters confronted Altman about hisprivate comment that upwards of 70%
of jobs could be eliminated by ai.
Altman just emphasized helping peoplebecome more productive, but his corporate
(15:55):
customers are telling a different story.
I. And this isn't theoretical anymore.
Besides the tech losses, there aresome other indicators by some reports.
January, 2025 saw the lowest jobopenings in professional services
since 2013, a 20% year over yeardrop Research shows that 40% of white
(16:17):
collar job seekers in 2024 failed tosecure interviews while high paying
positions hit decade low hiring levels.
It doesn't mean we're there yet, butit does mean that the signs are there.
So the disconnect is striking.
While other tech leaders are warningof impending white collar job crises
and actively reducing their workforces,the CEO of the company creating the
(16:39):
most advanced AI remains publiclyoptimistic about job creation.
But some could claim that Altman hasevery reason to soft pedal the impacts.
He wants to drive full steam ahead,and you don't have to be a conspiracy
theorist to believe that the USgovernment might not be telling us
the truth either, as they reportedlylook to decimate government ranks
(17:01):
using ai, but they desperately want toget AI implemented before China does.
Even those who claim there willbe big disasters as companies and
governments overreach the abilityof technology and have disastrous
implementations, they're right.
Every time we've had a majordevelopment in technology, we've made
(17:22):
big mistakes and somehow we muddleon and fix them, but we can fix.
Systems, and we might even beable to fix business problems.
But what we might not be able to fixis the social and societal impacts.
And if you think there's a hugeresentment caused by outsourcing
and automation in the past decades,will you see what happens if youth
(17:47):
unemployment were to hit the levels?
A Amodei predicts.
COVID unemployment was only about13% and that was devastating.
A Amodei is talking about20% youth unemployment.
We won't stop the on rush of ai.
That's not gonna happen.
We will have huge problems,some disasters, and potentially
(18:10):
a huge upending of even oureconomic system, we can't stop it.
But even if we can't stop it, we cantry to adapt to what's going to happen.
And in doing that, we're entitledto some straight talk from those
who know what's really happening.
(18:32):
We deserve it.
And that's our show.
Glad to be back with the news.
We'll have a shorter work week,sometimes over the summer, and some
repeat programming on some weekends.
Um, but we're back andbringing you the tech news.
I'm your host, Jim Love.
Have a marvelous Monday.
Staples Canada tackles themillion ton E-waste crisis.
A German model is 200% faster than deepseek scientists create the first quantum
operating system and the AI job crisis.
Who are you gonna believe,Sam Altman or your lying eyes?
Welcome to hashtag Trending.
(00:21):
I'm your host, Jim Love.
Let's get into it.
I can't believe I'm saying back toschool already, but as retailers
prepare for back to school shopping,staples Canada has launched a solution
that tackles two problems at once.
The financial strain of buyingnew tech and Canada's mounting
electronic waste crisis.
(00:42):
The new Staples Trade-in program letsCanadians exchange old smartphones,
laptops, and tablets for instantgift cards and for consumers who
might be a little freaked outabout the economic uncertainty and
grappling with increasing costs.
The idea of being able to trade inolder electronics has an appeal, but
(01:03):
there's an added benefit grapplingwith nearly 1 million tons of annual
E-waste created in Canada alone.
New research from the Universityof Waterloo reveals that Canada's
electronic waste has more thantripled in the last two decades.
Jumping from 8.3 kilograms per personin 2000 to 25.3 kilograms in 2020.
(01:28):
By 2030, Canadians are expectedto generate 1.2 million tons of
e-waste annually, equivalent tofilling the CN Tower 110 times.
Rachel Huckle, CEO of Staples, Canadasays The company is committed to making
it easier for consumers to access thelatest technology in a smarter and more
(01:52):
sustainable way, The program addresseswhat researchers call Canada's Forgotten
Repair Culture, where functional devicesare discarded simply for newer models.
Customers answer a few questionsonline about their device's condition,
and receive an immediate quote.
Once accepted, they get a Staples E-giftcard redeemable immediately at any
(02:15):
one of Canada's 298 Staples locations.
The old devices can either be droppedoff at their local store or shipped
directly to Allstate Staples partnerin the program using a prepaid label.
Allstate Protection Plans, powerswhat the company calls a circular
economy enablement, handling everythingfrom device valuation to certified
(02:39):
refurbishment and responsible recycling.
That's a win-win for customers',wallets, and the planet.
Staples joins a small group of retailersthat are tackling E-Waste head on
However, few major retailers haveintegrated trade-in value with immediate
purchasing power the way Staples have.
(02:59):
The program launches as back to schoolspending peaks when families are most
likely to upgrade devices for students.
It makes old tech immediatelyconvertible to purchasing power at
a time when families need it most,and as a person with a basement
full of tech too good to throw out,but with no place to see it reused.
(03:19):
This is a good idea.
The AI world is buzzingafter a 24-year-old German
consulting firm just dropped.
What developers are calling a holy sh Soa holy smokes, uh, level of innovation.
If you remember the sensation causedby the launch of Chinese AI deep
seek, which provided an open sourceAI with full weights, in essence,
(03:43):
pre-trained, that ran on what?
Compared to ChatGPT or otherswas a tiny hardware profile.
Developers claim that while training costsof ChatGPT and similar models could be
between 70 and a hundred million dollars.
They'd done all the training for under$6 million, but you don't need to worry
(04:03):
about that even because they shippedthe model with its weightings or the
training intact and the processingcosts of this model were a small
fraction of the larger frontier models,
It was and remains a bit of a miracle.
The US embargo restricted theChinese on how much and what
kind of GPUs they could buy.
(04:25):
Well, they made a virtue outta the problemand delivered what might be the most
efficient and cheapest frontier model.
And as the commercialsays, it's open source.
You can't save more money than free.
So where does anyone go from there?
Well, TNG Technology Consulting, aMunich based firm has released a new
(04:47):
version of Deep Seek TNGR one T twoChimera, and it's reportedly wait
for it 200% faster than deep seeks.
Latest.
R 1 5 2 8 while maintaining90% of its intelligence.
And did I mention they'regiving it away for free?
(05:10):
While OpenAI, Google and Anthropic Battlefor billions in funding TNG Technology
Consulting, a Munich based firm with800 employees just demonstrated that
breakthrough AI innovation doesn'trequire Silicon Valley budgets.
The secret weapon.
A technique called Assembly of Experts.
(05:31):
It merges the best part of multiple AImodels without expensive retraining.
There's a lot of hype in thisbusiness, but the excitement appears
at least, somewhat justified.
R one T two not only is free, not onlyis fast, but it achieves the speed boost
by generating responses using just 40% ofthe tokens required by its predecessors.
(05:56):
And tokens are the essential unitof processing, meaning dramatically
lower costs and faster responses.
TNGs breakthrough comes from thinkingdifferently about AI development.
Instead of training massive modelsfrom scratch, their assembly of experts
methods selectively combines thereasoning power of DeepSeek, R 1 0 5 2 8.
(06:19):
The structured thinking ofthe original R one and the
efficiency of their V 3 0 3 2 4.
The result is a model engineered tomaintain high reasoning capability
while significantly reducing inferencecost, inference being the process
that happens after the prompt.
(06:40):
Some have called it.
Automotive engineering applied to ai.
Rather than building a completely newengine, they've created a hybrid that
gets the performance of a V eight withthe efficiency of a four cylinder.
Now, this isn't justabout bragging rights.
The model maintains elite.
Performance on advanced reasoning tests.
Scoring between 90 and 92% of R 1 0 52 eight's results on mathematical and
(07:06):
graduate level problems while slashingoperational costs for enterprises.
This translates into runninga sophisticated AI application
at a fraction of the expense.
The timing is particularly strikingas major tech companies are announcing
massive AI infrastructure investments.
(07:26):
Microsoft is planning $80 billion inAI spending for 2025, while Amazon
is committing similar amounts.
meanwhile, TNG achieved thisbreakthrough using existing
models and clever engineering.
TNG is releasing R one T two underan MIT license, meaning any company
can use, Amodeify and deploy itcommercially without licensing fees.
(07:52):
The decision puts pressureon big tech firms charging
premium rates for AI access.
Why pay thousands monthly for APIcalls when you can run comparable
intelligence on your own infrastructure?
over to you Silicon Valley,
and if you've been around it longenough, you know that computers made
(08:13):
their way into common business usagewhen they had operating systems
that provided much needed interfacesbetween machine and programs.
It happened with mainframe computers,it happened with mini or departmental
computers, and most of us.
Of a certain age.
Remember MSDOS, the operating systemthat Bill Gates and Company developed
(08:33):
that powered the PC revolution?
Well, something similar hashappened for Quantum Computers.
An international research teamhas announced that they built
the brain for quantum machines asthey unveiled QNodeOS the world's
first operating system designedspecifically for Quantum computers.
(08:55):
The breakthrough published inNature could finally bridge the gap.
Between quantum computing's,theoretical promise and practical
applications enabling different typesof quantum computers to communicate
seamlessly for the first time.
Until now, quantum computers havebeen like brilliant, but isolated
(09:16):
scientists each speaking a differentlanguage and unable to collaborate.
QNodeOS solves this fundamental problemby creating a universal translator that
allows diverse quantum technologies.
From diamond based systems to trapped ionprocessors to work together in networks.
(09:38):
QNodeOS operates through twointegrated processing units
that work like a tag team.
There's the classical networkprocessing unit, and that handles
traditional computing tasks and programexecution while the Quantum Network
processing unit manages the exotic.
Quantum operations likeentanglement and superposition.
(10:00):
Together, they control quantumdevices through a unified interface.
The key innovation is what they'recalling the Q driver, a sophisticated
translator that converts universalcommands into specific instructions
for each type of Quantum hardware.
Think of it as creating a commonlanguage that lets Quantum computers
(10:21):
built with completely differenttechnologies, understand each other.
And
The researchers demonstrated QNodeOSScapabilities by connecting it to two
fundamentally different quantum systems.
One based on nitrogen vacancy centers inDiamond and another using trapped ions.
(10:41):
These systems work as differentlyas a Formula One race car and a
submarine, and yet QNodeOS enabledthem to coordinate seamlessly.
This breakthrough addresses a criticallimitation that's kept quantum computing
largely confined to research labs.
Previous quantum systems requiredphysicists to write custom code for
(11:03):
each specific experimental setup, likehaving to rewire your computer every time
you wanted to run a different program.
QNodeOS changes this by enabling highlevel programming, just like Windows
or Android do for classical computers.
Developers can now focus on creatingapplications rather than wrestling
with hardware complexities.
(11:24):
The Quantum Internet Allianceplans to deploy QNodeOS on their
Quantum Network Explorer providingresearchers worldwide access to
experiment with quantum networking.
This could accelerate development ofapplications we can barely imagine today.
From ultra secure communicationsto distributed quantum computing
that could solve problems currentlyimpossible for any classical computer.
(11:49):
Now there are still challenges.
The researchers are working to integrateprocessing units onto a single board
to eliminate a millisecond delaythat currently limits performance.
They're also developing long distanceprotocols and error correction methods
essential for practical quantum networks.
So we've all wondered when quantumcomputing might be able to solve
(12:09):
real world problems by solving theinteroperability problem, researchers
have created the foundation fora future quantum internet that
could revolutionize cryptography,chemistry, optimization, and maybe
even stuff we haven't yet discovered.
There will be areas where some jobsgo away, or maybe there'll be some
(12:30):
whole categories of jobs that go away.
That's OpenAI's, CEO, Sam Altmanadmitting the obvious in a recent podcast.
But then when asked if he agreed withAnthropic, CEO, Dario Amodei's, warning
that 50% of entry level white collarjobs could disappear within five years.
(12:51):
Altman said he disagreed.
His Chief Operating Officer, BradLightcap, was even more dismissive.
Claiming OpenAI has no evidence thatcompanies are wholesale replacing entry
level jobs with ai, and they talk to a lotof companies according to Brad, really.
Obviously he doesn't listen to thispodcast, but really does he actually
(13:14):
listen to the news this week?
Amazon's CEO Andy Jassy told his1.5 million employees in a memo.
We need fewer people doing some of thejobs that are being done today and more
people doing other types of jobs, but.
That's a little sugar coating.
He was brutally honest.
In the next few years, we expect thatthis will reduce our total corporate
(13:38):
workforce as we get efficiency gains fromusing AI extensively across the company.
Amazon has already cut27,000 jobs since 2022.
but Jassy isn't alone.
Microsoft has laid off over 15,000employees in 2025 alone, including their
(13:59):
director of AI apparently to free up $80billion for AI infrastructure investments.
But think about that.
The company that created a way to takeChatGPT to market is cutting people
to pay for the very technology thatmight replace them, and CEO Satya
Nadella is saying that about 30% oftheir code is being generated by AI
(14:25):
If you go through a list of othermajor CEOs, you'll hear similar
stories from Salesforce saying thatabout 50% of their work could be
done by AI to social media's Meta.
It's the same story Which brings us tothe other guy, Anthropic, CEO, Dario
Amodei, who delivered perhaps the starkestwarning, yet telling Axios that AI
could eliminate half of all entry levelwhite collar jobs within five years.
(14:50):
A move he said could cause unemploymentto spike to between 10 and 20%.
His message to lawmakers, most of themare unaware that this is about to happen.
It sounds crazy andpeople don't believe it.
Now you can claim a Amodei is mistaken.
(15:11):
You can claim that he's wrong, eventhough his company is on the leading
edge of delivering some of the work,replacing agents with a variety
of partners, and he admits he'snothing to gain from this prediction.
Actually, he probably has a lotto lose if there's a backlash
against AI because of what he said.
(15:33):
that brings us back to OpenAI's.
Sam Altman, is he reallytelling the whole truth?
Some claim he's changed his storyfrom time to time When Senator Gary
Peters confronted Altman about hisprivate comment that upwards of 70%
of jobs could be eliminated by ai.
Altman just emphasized helping peoplebecome more productive, but his corporate
(15:55):
customers are telling a different story.
I. And this isn't theoretical anymore.
Besides the tech losses, there aresome other indicators by some reports.
January, 2025 saw the lowest jobopenings in professional services
since 2013, a 20% year over yeardrop Research shows that 40% of white
(16:17):
collar job seekers in 2024 failed tosecure interviews while high paying
positions hit decade low hiring levels.
It doesn't mean we're there yet, butit does mean that the signs are there.
So the disconnect is striking.
While other tech leaders are warningof impending white collar job crises
and actively reducing their workforces,the CEO of the company creating the
(16:39):
most advanced AI remains publiclyoptimistic about job creation.
But some could claim that Altman hasevery reason to soft pedal the impacts.
He wants to drive full steam ahead,and you don't have to be a conspiracy
theorist to believe that the USgovernment might not be telling us
the truth either, as they reportedlylook to decimate government ranks
(17:01):
using ai, but they desperately want toget AI implemented before China does.
Even those who claim there willbe big disasters as companies and
governments overreach the abilityof technology and have disastrous
implementations, they're right.
Every time we've had a majordevelopment in technology, we've made
(17:22):
big mistakes and somehow we muddleon and fix them, but we can fix.
Systems, and we might even beable to fix business problems.
But what we might not be able to fixis the social and societal impacts.
And if you think there's a hugeresentment caused by outsourcing
and automation in the past decades,will you see what happens if youth
(17:47):
unemployment were to hit the levels?
A Amodei predicts.
COVID unemployment was only about13% and that was devastating.
A Amodei is talking about20% youth unemployment.
We won't stop the on rush of ai.
That's not gonna happen.
We will have huge problems,some disasters, and potentially
(18:10):
a huge upending of even oureconomic system, we can't stop it.
But even if we can't stop it, we cantry to adapt to what's going to happen.
And in doing that, we're entitledto some straight talk from those
who know what's really happening.
(18:32):
We deserve it.
And that's our show.
Glad to be back with the news.
We'll have a shorter work week,sometimes over the summer, and some
repeat programming on some weekends.
Um, but we're back andbringing you the tech news.
I'm your host, Jim Love.
Have a marvelous Monday.
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