August 9, 2025 • 24 mins
"What if 2026 is the year the future truly arrives?"
Step into tomorrow with this thrilling deep dive into 17 emerging technology trends that are set to redefine every corner of our lives. From AI automating your morning routine before you even wake up, to quantum computing solving problems in seconds that used to take years, this is the roadmap to the world we’ve only dreamed about.
We unpack the rise of low-code/no-code platforms empowering anyone to build apps, the leap of extended reality (XR) into AI-generated worlds, and AI-native operating systems that could run everything from your home to your city. Discover how Edge AI chips, wearable tech upgrades, and brain-computer interfaces might make science fiction look outdated by comparison.
With AI-powered robots revolutionizing retail and logistics, privacy-first AI processing protecting your data, and personalized healthcare AI tailoring treatments just for you, this isn’t just a forecast—it’s a warning, an invitation, and a wake-up call all in one.
Whether you’re a tech visionary, a cautious skeptic, or just wondering when AR glasses will finally replace your smartphone, this episode delivers the insights you’ll need to navigate—and maybe even dominate—the AI-driven world of 2026.
Listen now and stay ahead—because in the future, those who understand the tech will write the rules.
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Become a supporter of this podcast: https://www.spreaker.com/podcast/tech-threads-sci-tech-future-tech-ai--5976276/support.
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Step into tomorrow with this thrilling deep dive into 17 emerging technology trends that are set to redefine every corner of our lives. From AI automating your morning routine before you even wake up, to quantum computing solving problems in seconds that used to take years, this is the roadmap to the world we’ve only dreamed about.
We unpack the rise of low-code/no-code platforms empowering anyone to build apps, the leap of extended reality (XR) into AI-generated worlds, and AI-native operating systems that could run everything from your home to your city. Discover how Edge AI chips, wearable tech upgrades, and brain-computer interfaces might make science fiction look outdated by comparison.
With AI-powered robots revolutionizing retail and logistics, privacy-first AI processing protecting your data, and personalized healthcare AI tailoring treatments just for you, this isn’t just a forecast—it’s a warning, an invitation, and a wake-up call all in one.
Whether you’re a tech visionary, a cautious skeptic, or just wondering when AR glasses will finally replace your smartphone, this episode delivers the insights you’ll need to navigate—and maybe even dominate—the AI-driven world of 2026.
Listen now and stay ahead—because in the future, those who understand the tech will write the rules.
You May also Like:
✨Sky Near Me
Live map of stars & planets visible near you
📌Debt Planner App
Your Path to Debt-Free Living
Become a supporter of this podcast: https://www.spreaker.com/podcast/tech-threads-sci-tech-future-tech-ai--5976276/support.
You May also Like:
🎁The Perfect Gift App
Find the Perfect Gift in Seconds
⭐Sky Near Me
Live map of stars & planets visible near you
✔Debt Planner App
Your Path to Debt-Free Living
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:00):
Imagine stepping into a tomorrow that isn't, you know, decades away,
but it's unfolding right now around you, almost invisibly. A
tomorrow where your car maybe anticipates your next turn before
you even think it, or your doctor uses AI to
spot illness way before symptoms show up. Or maybe even
a future where you could control a computer with just
(00:21):
a thought. Sounds like sci fi, right, like something from
a movie. Well, what our latest deep dive into the
research reveals is that this isn't really science fiction anymore.
It's here, and it's rapidly reshaping pretty much everything that's
exactly right.
Speaker 2 (00:35):
And for this deep dive, our mission really is to
cut through all the noise. We want to sift through
the latest insights, the analyzes and distill what's truly critical,
which developments are actively sculpting our immediate future. We want
to give you a clear understanding of what's genuinely happening
beyond the headlines.
Speaker 1 (00:51):
And what we're unpacking today is well, it's kind of breathtaking. Honestly.
The material we've looked at maps out seventeen significant technological
trends seventeen all projected to deeply impact things by twenty
twenty six. That's really soon. So it's not just a glance.
It feels more like a preview, doesn't It a front
row seat to how we'll be living and working very
(01:12):
very soon exactly?
Speaker 2 (01:13):
And when you zoom out look at the big picture predictions,
one statistic really just jumps out. By twenty twenty six,
AI could automate up to get this seventy percent of
everyday work.
Speaker 1 (01:24):
Tasks seventy percent. Wow. Okay, hold on, that's huge. That's
not just like adjusting our routines. That sounds like a
complete restructuring of how work even happens.
Speaker 2 (01:33):
It really is. It's foundational, from basic, repetitive stuff to
much more complex decisions. That single prediction sets a really
powerful context for everything else we're going to talk about.
It hints at these massive shifts already underway.
Speaker 1 (01:44):
Okay, let's really unpack this then, because the scale of
automation you're talking about is Yeah, it's astounding. We're not
just automating one little task here and there anymore, are we?
This sounds like reshaping entire workflows, how we build tools,
even how we create things, articles or videos. It feels
like a major paradigm shift.
Speaker 2 (02:03):
It is, and what's truly fascinating isn't just automating the
task itself, but how things get built and managed who
gets to build them. Even this first section really shows
how technology is just breaking down those traditional barriers, barriers
to creation, to efficiency, empowering people who aren't necessarily deep
tech experts.
Speaker 1 (02:22):
Okay, so democratizing creation. Yeah, that leads perfectly into the
first trend, right, the rise of low code and no
code development. For so long, building an app or a
website felt like you absolutely had to be a code
or a software engineer exactly.
Speaker 2 (02:34):
It was this exclusive domain. But the sources are showing
something groundbreaking. By twenty twenty six, the projection is over
seventy five percent of new applications will be built using
these low code or no code platforms.
Speaker 1 (02:45):
Seventy five percent in just two years. That's incredible acceleration.
Speaker 2 (02:49):
It is the core idea is democratizing software creation. Platforms
like Glide, Bubble, Microsoft Power apps. They're maturing users don't
need to write traditional code. It's more like drag, drop, publish.
And it's not just simple tools. Think about open AI's
custom GPTs. People with zero coding knowledge can build their
(03:09):
own AI tools now.
Speaker 1 (03:11):
Right, tailored AI experiences without.
Speaker 2 (03:13):
Programming, yeah, or Google's app sheet letting businesses automate whole
workflows without hiring developers. The implication is huge. It lowers
the barrier to innovation, speeds everything up. Businesses, small teams,
even individuals can prototype and deploy custom solutions really fast.
It changes the role of it too, from builders to
more like curators.
Speaker 1 (03:33):
That is a staggering change in how things get built.
And if apps can be spun up that quickly, well,
it naturally leads to the next point, doesn't it workflow
automation at scale, So we're moving beyond just automating one
task like sending an.
Speaker 2 (03:46):
Email precisely, we're talking about orchestrating entire end to end
organizational workflows. Imagine a whole business process from start to finish,
largely handled by machines.
Speaker 1 (03:55):
Okay, like what kind of processes?
Speaker 2 (03:56):
Think about onboarding and new employee, All the steps involved,
more processing invoices, managing complex supply chains. Tools like service now, uipaths,
Zapier they facilitate this, and the efficiency gains are significant.
Service Now users, for example, reported up to a sixty
five percent reduction in repetitive work in big companies.
Speaker 1 (04:14):
Sixty five percent reduction.
Speaker 2 (04:15):
Wow, and this isn't just theory. Look at Amazon's warehouses.
They're already using predictive analytics to coordinate humans and robots seamlessly.
The implication whole process is running autonomously. It transforms efficiency,
reduces errors, and lets people focus on more strategic, uniquely
human work. Shifting from doer to overseer.
Speaker 1 (04:36):
That's an incredible leap. And building on that idea of economy,
we get to AI agents that work for you. This
sounds like AI going from just responding to prompts to
actually doing the whole job exactly.
Speaker 2 (04:46):
It's a monumental leap. AI transitions from being a helpful
assistant you chat with to an independent entity that handles
full tasks start to finish, often with minimal human input
after the initial goal is set. It's like having a
truly intuitive digital employee.
Speaker 1 (05:00):
Can you give an example that sounds quite advanced?
Speaker 2 (05:03):
Well, A really striking one from twenty twenty four was Devin,
an AI software engineer from Cognition Labs. It was demoed
building a full website from just a high level request.
It debugged its own code, fixed errors and deployed it
live autonomously.
Speaker 1 (05:18):
Wow. So it wasn't just suggesting code, it was actually
building and troubleshooting.
Speaker 2 (05:22):
Yes, and beyond coding, tools like otter GPT can chain
tasks like plan a complex strip, book the reservations on
different sites and then send you the summary.
Speaker 1 (05:32):
Okay, that's seriously useful.
Speaker 2 (05:33):
And businesses are training these agents for things like employee onboarding,
data management, even client responses. So the implication is this
fundamental shift from chatting with AI to delegating to AI.
Truly autonomous digital assistants are emerging.
Speaker 1 (05:47):
And if these AI agents are doing more and AI
is building more tools, it feels like AI's output will
be everywhere.
Speaker 2 (05:54):
Which brings us to generative AI becomes default is the
idea that most digital stuff we see here or read
will soon be AI influencder AI created. That's pretty much it.
By twenty twenty six, it's projected that a vast majority
of digital content will have Generative AI's fingerprints on it,
if not being directly created by it. It's not just
(06:14):
a feature anymore. It's becoming woven into the fabric of
content creation.
Speaker 1 (06:17):
How so what's driving that?
Speaker 2 (06:19):
Well, you have major players like OpenAI, Google Anthropic pushing
the limits with large multimodal models GPT five, Gemini Ultra.
These things can handle text, images, video audio, all within
one conversation. It makes creation incredibly fluid.
Speaker 1 (06:35):
Right.
Speaker 3 (06:35):
Multimodal is a big deal, and we see it in
commercial tools already, Aderby's Firefly and video editing Runway mL
for cinematic stuff, Eleven Labs cloning voices in second.
Speaker 1 (06:46):
That voice cloning is almost unnerving. Sometimes it is.
Speaker 2 (06:49):
But the implication is massive. Generative AI is set to
redefine content creation across almost every industry, writing articles, marketing, copy,
producing podcasts like this one, even crafting verse experiences. It
means creation becomes much more of a human AI collaboration,
which you know, raises interesting questions about authorship and creativity itself.
Speaker 1 (07:07):
Okay, so that covers the automation side. Now here's where
for me it gets really interesting. This idea that the
line between our physical world and the digital world is
blurring and blurring fast. It's not just about smart devices anymore,
is it. It's like the environment itself is becoming smart, reactive.
Speaker 2 (07:26):
Exactly, and connecting this to the bigger picture, these trends
aren't just about new gadgets. They represent entirely new ways
of experiencing and managing our physical and digital surroundings. It
definitely makes you question how even define reality when the
digital is so seamlessly integrated. You know, we're essentially building
intelligent layers right over the physical world, which.
Speaker 1 (07:47):
Takes us straight into AI crafted experience and extended reality. XR,
so VR and AR. They've been around mainly for games
or specific industries, but this sounds different. Intelligent self generating.
Speaker 2 (07:58):
Spaces, Yeah, moving beyond just a visual display. The ideas
that XR spaces won't just be static environments you visit,
they'll generate themselves, adapt based on what you do, who
you are, creating these incredibly dynamic interactions. How wod that
actually work well in videos? Already creating real time characters
in XR that can hold full, unscripted conversations, they feel
(08:18):
incredibly real. META is investing heavily in avatars that don't
just look good, but react, emote, improvise, making digital interactions
feel much more human, like.
Speaker 1 (08:29):
They understand social cues something like that.
Speaker 2 (08:32):
And think about the virtual shops shown at cees. They
could change their layout in real time based on how
people moved around inside them. The implication is much more immersive, dynamic,
personalized digital experiences that adapt instantly to you. It's moving
from just being there to the space being with you.
Speaker 1 (08:49):
And if virtual spaces are getting smarter, so are physical ones. Right,
let's talk about smart infrastructure and IoT two point zero.
This isn't just my smart thermostatus. We're talking city wide
intelligence exactly.
Speaker 2 (09:00):
It's a massive expansion. Think beyond individual gadgets to interconnected
devices creating intelligent, self optimizing physical environments on a huge scale.
The prediction is staggering over thirty billion IoT devices globally
by twenty twenty six.
Speaker 1 (09:15):
Thirty billion. Okay, so what does that actually enable.
Speaker 2 (09:17):
We're seeing it already. Traffic lights in Singapore that adjust
in real time to congestion based on live data. It
significantly improves traffic flow.
Speaker 1 (09:26):
Right, I've heard about that.
Speaker 2 (09:27):
Or warehouses using tech from a TOWUS or Verizon for instant,
human free inventory tracking, optimizing logistics like never before. And
in South Korea they have these smart poles doing multiple things,
monitoring air quality, providing Wi Fi charging phones.
Speaker 1 (09:43):
Huh, infrastructure doing more.
Speaker 2 (09:45):
Precisely, so cities, industrial complexes become more efficient, responsive, data
driven potential for less waste, better quality of life. It's
like a foundational layer for smart living.
Speaker 1 (09:56):
This blending of digital and physical. It feels like it's
going to change how we even access information, which brings
us to AR glasses replace screens. AR glasses have felt
like they're just around the corner for years. Is this
finally it? Or are they becoming practical?
Speaker 2 (10:12):
The sources strongly suggest yes, they're reaching a point of
practical usefulness where they could genuinely reduce the need to
constantly pull out your phone.
Speaker 1 (10:19):
So what makes now different?
Speaker 2 (10:20):
Well, Apple's vision pro, while maybe bulky and expensive for now,
definitely kicked things into high gear. It showed what's possible.
Now you have Meta XR, Reel, Samsung all working hard
on lighter, more practical.
Speaker 1 (10:33):
AR glasses, and what could they do.
Speaker 2 (10:35):
Imagine real time captions appearing in your vision during a
conversation or navigation, arrows overlaid directly onto the street as you.
Speaker 1 (10:42):
Walk, or even translated subtitles floating there when someone speaks.
Speaker 2 (10:45):
Another language exactly, and the key is AI handling the context.
The glasses might anticipate what info you need before you ask.
The implication is this seamless information layer over the world,
transforming how we access digital content, making it ambient, contextual,
always there, but not intrusive, like a digital sixth sense.
Speaker 1 (11:06):
And these intelligent layers, they're coming into our homes too,
aren't they, Which is AI powered home assistance. We have
smart speakers now, but this sounds like robots in the house.
Speaker 2 (11:15):
It's definitely an evolution beyond just a voice in a box.
They're becoming mobile, versatile, more intelligent home robots, a physical
presence that can move and interact with the.
Speaker 1 (11:24):
Environment, like Rosy, the robot from the Jetsons. Are we
there yet?
Speaker 2 (11:27):
Maybe not quite Rosy, But look at Amazon's astro introduced
in twenty twenty one. It's been getting smarter. It's already
used for home patrol, elder care assistants, even delivering small
items on command in homes and offices.
Speaker 1 (11:41):
Okay, so practical uses are emerging.
Speaker 2 (11:43):
Yeah, and Apple's rumored to be working on a tabletop robot,
maybe for dynamic FaceTime calls. In China, you see humanoid
assistance in showrooms already interacting with customers. They're moving beyond
just voice. They have screens, wheels, arms, sometimes even facial expressions.
So the implication is a greater physical presence, more functional capability,
(12:03):
integrating deeper into our daily routines. They're becoming more like
active members of the household.
Speaker 1 (12:08):
Okay, so we've covered automation and the physical world getting smarter.
What does this all mean for us personally? Yeah, it
feels like tech is getting incredibly close, almost invisible, but
really impactful, especially health.
Speaker 2 (12:21):
Privacy, right, and that raises really important questions, doesn't it.
How do we navigate a world where tech understands us
so intimately, even biologically, and crucially, how do we make
sure our privacy or autonomy keeps pace. It's that balance
between incredible convenience and protecting sensitive information.
Speaker 1 (12:40):
And the first place this hits home is wearables that
know you better than you do. We've gone from step
counters to pretty sophisticated health monitors already, but this sounds
like another level entirely.
Speaker 2 (12:51):
It really is devices like or rings, whoop bands. They
already give detailed recovery scores, sleep analysis, stress metrics, actionable insights.
The emerging stuff is revolutionary non invasive blood sugar tracking.
Imagine that for diabetics, no more finger.
Speaker 1 (13:06):
Pricks that would be life changing for millions.
Speaker 2 (13:08):
Absolutely, companies like Mavena are working on continuous blood pressure wearables.
Some smart rings can even detect tiny skin temperature changes
before you feel sick, giving early warnings for illness.
Speaker 1 (13:18):
Wow, predicting illness.
Speaker 2 (13:20):
It seems like it, And the crucial part is the AI.
It's not just raw data that AI analyzes. It gives
personalized nudges predictions. Instead of just U slaped seven hours.
It might analyze months of data and suggest specific routine
changes for better recovery based on your patterns. So the
implication is the shift to proactive health management, early detection,
(13:40):
personalized wellness guidance, moving from reactive healthcare to preventative optimized.
Speaker 1 (13:45):
Well being and building right on that. Personal health data
is AI and healthcare gets personal. This sounds like AI
moving into the formal healthcare system.
Speaker 2 (13:54):
Diagnosis treatment, Yes, revolutionizing diagnosis, risk prediction and personalized treatment,
making medicine more precise proactive. The diagnostic breakthroughs are stunning.
In twenty twenty four, Google deepminds AI could spot twenty
one diseases just from retinal scans, often earlier than doctors.
Speaker 1 (14:10):
Twenty one diseases from an eye scan.
Speaker 2 (14:12):
Yeah, picking up patterns humans might miss. And hospitals in
the US are using AI to analyze patient data to
predict sepsis or cardiac risk hours before symptoms are obvious,
allowing critical early intervention. I could save so many lives definitely,
And in cancer treatment, AI is helping create personalized chemotherapy
plans based on an individual specific genetic makeup, moving way
(14:32):
beyond one size fits all. So the implication is more
accurate earlier diagnoses, proactive intervention, tailored treatments, leading to better
patient outcomes and a more efficient system.
Speaker 1 (14:42):
Okay, but with all this incredibly sensitive health data being used,
privacy becomes a massive concern, doesn't it, which leads us
to privacy first, AI and local processing? Is this about
AI doing its work on my device, not in the
cloud exactly?
Speaker 2 (14:57):
It's a really significant shifts tasks directly on your phone,
your laptop, you're wearable, driven by demands for both privacy
and speed keeping your data close.
Speaker 1 (15:06):
How is that possible? Doesn't AI need massive computing power?
Speaker 2 (15:10):
Well, the chip makers are building hardware specifically for this.
Apple's new chips, the A seventeen pro the M four.
They handle complex AI tasks right on the device, no
cloud upload needed from many things Metaslama three models can
run locally too. Intel's Meteor Lake chips have built in
AI accelerators and PUS neural processing units. Yeah, specialized circuits
for efficient AI calculations using less power and regulations like
(15:33):
GDPR in Europe CCPA in California. They're pushing development this
way too, towards offline on device processing. So the implication
is better privacy, faster processing, no cloud lag, and AI
that learns to keep your data private.
Speaker 1 (15:47):
It builds trust, and if AI is running locally efficiently,
it can become much more integrated into everything we do
on our devices. Yeah, which is AI native operating system,
So not just AI and apps, but the whole OS
becoming intelligent.
Speaker 2 (16:01):
Precisely. We see hints now like predictive text or autocorrect,
but this is deeper AI intelligence woven into the OS itself,
providing system wide help. Microsoft is testing c Pilot and
Windows eleven. You can ask your desktop to summarize files,
rewrite emails, generate images without switching apps.
Speaker 1 (16:18):
Ah, So the OS itself becomes the.
Speaker 2 (16:20):
Assistant kind of Yeah, a dynamic partner, not just a
static interface. Apple's expected to announce more AI native features
in mac os and iOS too, running on those new
neural engines. The implication your whole computer system gets smarter,
more proactive thinking with you, enhancing productivity, making interactions more intuitive,
moving from a tool you command to a partner that anticipates,
(16:42):
and this.
Speaker 1 (16:42):
Deep integration, this on device intelligence. It all depends on
the hardware, right, which is why we have jaichips everywhere.
The idea that pretty much any new device will have
a dedicated aichip.
Speaker 2 (16:53):
That's the strong trend. Yes, the next phone or laptop
you buy, chances are it'll have an AI chip built in.
This EDGAI means real time smarts right there on your device,
no cloud lag.
Speaker 1 (17:03):
So what do these chips actually enable on the device.
Speaker 2 (17:05):
Things like instant language translations, sophisticated image editing, really nuanced
voice recognition, all happening locally. Apple's A seventeen pro M
four chips do this. Qualcom Snapdragon x Elite brings it
to Windows laptops. Intel's meteor La like chips with those
MPUs handle AI efficiently even low power tasks. The implication
(17:26):
is every device becoming its own little brain. Capable of
complex AI locally enhancing speed, privacy, efficiency, making smart features
instant and personal.
Speaker 1 (17:36):
Okay, this next section, honestly it feels like it's straight
out of science fiction. Yeah, but the sources are telling
us this stuff is happening now. It's accelerating incredibly fast,
robots walking among us, machines reading thoughts. It's kind of
challenging our basic notions of what's possible.
Speaker 2 (17:51):
It really is, And what's fascinating is how quickly these
things are moving from theory or labs to actual practical application,
especially in areas people thought were still decades away. It
definitely raises big questions about our future collaboration with machines,
doesn't it. How do our rules evolve when machines become
so capable?
Speaker 1 (18:07):
Which leads us to AI enhanced robotics In retail and logistics.
We've seen factory robots, but this sounds like robots becoming
much more common and smarter in places like shops and warehouses.
Speaker 2 (18:18):
Yes, moving beyond simple, repetitive tasks to more intelligent, adaptive roles.
They're not just pre programmed anymore. We're seeing real deployments.
Agility robotics put its digit robot in Amazon warehouses in
twenty twenty four. It's bipedal designed to work alongside people.
Speaker 1 (18:36):
Walking robot in Amazon.
Speaker 2 (18:37):
Yeah, and Walmart's using autonomous shelf scanners in over one
thousand stores for real time inventory. You see those little
Starship or Kiwied delivery bots on college campuses. They're navigating
complex environments autonomously, and the key is they use AI
vision real time mapping, and they learn getting smarter over time.
Worker shortages are accelerating adoption too. They're becoming indispensable tools,
(19:00):
not just novelties. So the implication is robots becoming essential
intelligent parts of these sectors, changing operations and augmenting human work, and.
Speaker 1 (19:07):
Then taking it even further. Humanoid robots go commercial. This
is the one that really feels like sci fi. Becoming
real robots that look and move like us working.
Speaker 2 (19:18):
It's a massive step and it's happening. They're moving out
of labs into commercial settings doing practical tasks. Figure ai
partnered with BMW in twenty twenty four to put its
humanoid robot Figure one into car manufacturing.
Speaker 1 (19:31):
Wow in a car factory.
Speaker 2 (19:33):
Yes Agilities, digit is in logistics Tessel's optimis while still developing,
is already doing basic factory tasks like sorting parts, folding things.
The key is they can now walk, stably, lift things,
perform tasks with enough dexterity to be genuinely useful.
Speaker 1 (19:49):
But aren't the incredibly expensive.
Speaker 2 (19:51):
That's the other crucial factor. They're becoming economically viable. Projections
suggest some models could cost less than a small car
by twenty twenty six. That makes scaling possible, implication a
potential scalable humanoid workforce, augmenting human labor, especially for dangerous
or repetitive jobs.
Speaker 1 (20:07):
Okay, from humanoid robots to something even more out there.
Quantum computing nears utility. It's always sounded like theoretical physics
decades away. Is it actually getting close to being useful?
Speaker 2 (20:16):
The sources suggests Yes, it's rapidly approaching practical utility for specific,
very complex problems. It's moving from hypothesis to engineered reality.
IBM hit one thousand cubits in twenty twenty three, aiming
for over thirteen hundred this year. That's a huge milestone.
Speaker 1 (20:33):
Quibits, Yeah, they're the quantum equivalent of bits, right.
Speaker 2 (20:36):
Yeah, but fragile, exactly, very fragile which is why the
work on error correction is so critical. IBM and others
are making progress there, which is key to making them
reliable for real applications. And the potential uses are groundbreaking.
Simulating molecules for drug discovery at speeds impossible for classical computers,
revolutionizing medicine material science.
Speaker 1 (20:56):
Okay, so specialized high impact areas first yes.
Speaker 2 (20:59):
Or optimized incredibly complex systems like global supply chains, things
that overwhelm current supercomputers. Google, Io and q Righetti are
all racing ahead too. It's still early days for general use,
but the demos are concrete. The pace is quickening, It
hints it solving previously unsolvable problems.
Speaker 1 (21:15):
And finally, the one that pushes the boundaries, the furthest
maybe the most intimately, the rise of Brain Computer Interfaces
BCIs connecting the brain directly to computers. This isn't just
research anymore.
Speaker 2 (21:29):
No, it's decisively transitioning to real world clinical applications, enabling
direct communication, a neural bridge between brain and device, bridging
thought and digital control.
Speaker 1 (21:40):
That sounds profound, it is.
Speaker 2 (21:42):
The landmark event was early twenty twenty four, Neuralink confirmed
its first human cheap implant that person could control a
computer cursor just by thinking.
Speaker 1 (21:51):
Wow, just by thinking yeah.
Speaker 2 (21:53):
And while neuralink is invasive, other companies like synchron Precision
Neuroscience are developing less invasive methods, often aimed at restoring
function for people with paralysis, giving them back mobility or communication.
Speaker 1 (22:04):
The real medical breakthroughs are happening absolutely.
Speaker 2 (22:07):
Clinical trials have seen stroke patients regain limb control using
BCIs or send messages just through thought bypassing damaged nerves.
The implication is massive and not theoretical anymore. Bridging thought
in digital control offers huge potential for medicine for restoring
lost function, but also fundamentally redefines human computer interaction itself,
(22:28):
the ultimate interface.
Speaker 1 (22:30):
Wow. Okay, that was an incredible journey through those seventeen trends.
It really is mind boggling, isn't it to think these
aren't distant predictions, but things happening right now, unfolding around
is It almost feels like living in the sci fi story.
Speaker 2 (22:42):
It really does, and what we've covered highlights just how
pervasive these shifts are. From how we work and create
thanks to automation and AI, to how we interact with
our environment through smart infrastructure and ar, and even down
to the deeply personal our health, our privacy, maybe even
our thoughts with wearables and BCIs. These aren't just tech upgrades.
They're fundamental redefinitions of our relationship with technology and maybe
(23:04):
even with ourselves.
Speaker 1 (23:05):
And that's exactly why understanding this stuff isn't just interesting,
it feels crucial. Now. Hopefully this deep dive gave you
not just information, but real insights into the currents shaping
your daily life, your work, your wellness in the very
near future. It's about being informed, prepared, ready to navigate
this evolving landscape.
Speaker 2 (23:24):
And as technology gets better at anticipating our needs, operates
autonomously around us, even connects directly with our thoughts, it
leaves us with a really profound question to think about,
doesn't it. What does this all mean for things like
human intuition, our creativity, maybe even the definition of consciousness itself.
When our minds can start to seamlessly extend into the
(23:45):
digital realm.
Speaker 1 (23:46):
That is a powerful thought to end on. We really
hope you'll reflect on which of these trends resonated most
with you, or how you see them impacting your own life,
your community, your work in the coming couple of years,
the conversation really is just beginning.
Imagine stepping into a tomorrow that isn't, you know, decades away,
but it's unfolding right now around you, almost invisibly. A
tomorrow where your car maybe anticipates your next turn before
you even think it, or your doctor uses AI to
spot illness way before symptoms show up. Or maybe even
a future where you could control a computer with just
(00:21):
a thought. Sounds like sci fi, right, like something from
a movie. Well, what our latest deep dive into the
research reveals is that this isn't really science fiction anymore.
It's here, and it's rapidly reshaping pretty much everything that's
exactly right.
Speaker 2 (00:35):
And for this deep dive, our mission really is to
cut through all the noise. We want to sift through
the latest insights, the analyzes and distill what's truly critical,
which developments are actively sculpting our immediate future. We want
to give you a clear understanding of what's genuinely happening
beyond the headlines.
Speaker 1 (00:51):
And what we're unpacking today is well, it's kind of breathtaking. Honestly.
The material we've looked at maps out seventeen significant technological
trends seventeen all projected to deeply impact things by twenty
twenty six. That's really soon. So it's not just a glance.
It feels more like a preview, doesn't It a front
row seat to how we'll be living and working very
(01:12):
very soon exactly?
Speaker 2 (01:13):
And when you zoom out look at the big picture predictions,
one statistic really just jumps out. By twenty twenty six,
AI could automate up to get this seventy percent of
everyday work.
Speaker 1 (01:24):
Tasks seventy percent. Wow. Okay, hold on, that's huge. That's
not just like adjusting our routines. That sounds like a
complete restructuring of how work even happens.
Speaker 2 (01:33):
It really is. It's foundational, from basic, repetitive stuff to
much more complex decisions. That single prediction sets a really
powerful context for everything else we're going to talk about.
It hints at these massive shifts already underway.
Speaker 1 (01:44):
Okay, let's really unpack this then, because the scale of
automation you're talking about is Yeah, it's astounding. We're not
just automating one little task here and there anymore, are we?
This sounds like reshaping entire workflows, how we build tools,
even how we create things, articles or videos. It feels
like a major paradigm shift.
Speaker 2 (02:03):
It is, and what's truly fascinating isn't just automating the
task itself, but how things get built and managed who
gets to build them. Even this first section really shows
how technology is just breaking down those traditional barriers, barriers
to creation, to efficiency, empowering people who aren't necessarily deep
tech experts.
Speaker 1 (02:22):
Okay, so democratizing creation. Yeah, that leads perfectly into the
first trend, right, the rise of low code and no
code development. For so long, building an app or a
website felt like you absolutely had to be a code
or a software engineer exactly.
Speaker 2 (02:34):
It was this exclusive domain. But the sources are showing
something groundbreaking. By twenty twenty six, the projection is over
seventy five percent of new applications will be built using
these low code or no code platforms.
Speaker 1 (02:45):
Seventy five percent in just two years. That's incredible acceleration.
Speaker 2 (02:49):
It is the core idea is democratizing software creation. Platforms
like Glide, Bubble, Microsoft Power apps. They're maturing users don't
need to write traditional code. It's more like drag, drop, publish.
And it's not just simple tools. Think about open AI's
custom GPTs. People with zero coding knowledge can build their
(03:09):
own AI tools now.
Speaker 1 (03:11):
Right, tailored AI experiences without.
Speaker 2 (03:13):
Programming, yeah, or Google's app sheet letting businesses automate whole
workflows without hiring developers. The implication is huge. It lowers
the barrier to innovation, speeds everything up. Businesses, small teams,
even individuals can prototype and deploy custom solutions really fast.
It changes the role of it too, from builders to
more like curators.
Speaker 1 (03:33):
That is a staggering change in how things get built.
And if apps can be spun up that quickly, well,
it naturally leads to the next point, doesn't it workflow
automation at scale, So we're moving beyond just automating one
task like sending an.
Speaker 2 (03:46):
Email precisely, we're talking about orchestrating entire end to end
organizational workflows. Imagine a whole business process from start to finish,
largely handled by machines.
Speaker 1 (03:55):
Okay, like what kind of processes?
Speaker 2 (03:56):
Think about onboarding and new employee, All the steps involved,
more processing invoices, managing complex supply chains. Tools like service now, uipaths,
Zapier they facilitate this, and the efficiency gains are significant.
Service Now users, for example, reported up to a sixty
five percent reduction in repetitive work in big companies.
Speaker 1 (04:14):
Sixty five percent reduction.
Speaker 2 (04:15):
Wow, and this isn't just theory. Look at Amazon's warehouses.
They're already using predictive analytics to coordinate humans and robots seamlessly.
The implication whole process is running autonomously. It transforms efficiency,
reduces errors, and lets people focus on more strategic, uniquely
human work. Shifting from doer to overseer.
Speaker 1 (04:36):
That's an incredible leap. And building on that idea of economy,
we get to AI agents that work for you. This
sounds like AI going from just responding to prompts to
actually doing the whole job exactly.
Speaker 2 (04:46):
It's a monumental leap. AI transitions from being a helpful
assistant you chat with to an independent entity that handles
full tasks start to finish, often with minimal human input
after the initial goal is set. It's like having a
truly intuitive digital employee.
Speaker 1 (05:00):
Can you give an example that sounds quite advanced?
Speaker 2 (05:03):
Well, A really striking one from twenty twenty four was Devin,
an AI software engineer from Cognition Labs. It was demoed
building a full website from just a high level request.
It debugged its own code, fixed errors and deployed it
live autonomously.
Speaker 1 (05:18):
Wow. So it wasn't just suggesting code, it was actually
building and troubleshooting.
Speaker 2 (05:22):
Yes, and beyond coding, tools like otter GPT can chain
tasks like plan a complex strip, book the reservations on
different sites and then send you the summary.
Speaker 1 (05:32):
Okay, that's seriously useful.
Speaker 2 (05:33):
And businesses are training these agents for things like employee onboarding,
data management, even client responses. So the implication is this
fundamental shift from chatting with AI to delegating to AI.
Truly autonomous digital assistants are emerging.
Speaker 1 (05:47):
And if these AI agents are doing more and AI
is building more tools, it feels like AI's output will
be everywhere.
Speaker 2 (05:54):
Which brings us to generative AI becomes default is the
idea that most digital stuff we see here or read
will soon be AI influencder AI created. That's pretty much it.
By twenty twenty six, it's projected that a vast majority
of digital content will have Generative AI's fingerprints on it,
if not being directly created by it. It's not just
(06:14):
a feature anymore. It's becoming woven into the fabric of
content creation.
Speaker 1 (06:17):
How so what's driving that?
Speaker 2 (06:19):
Well, you have major players like OpenAI, Google Anthropic pushing
the limits with large multimodal models GPT five, Gemini Ultra.
These things can handle text, images, video audio, all within
one conversation. It makes creation incredibly fluid.
Speaker 1 (06:35):
Right.
Speaker 3 (06:35):
Multimodal is a big deal, and we see it in
commercial tools already, Aderby's Firefly and video editing Runway mL
for cinematic stuff, Eleven Labs cloning voices in second.
Speaker 1 (06:46):
That voice cloning is almost unnerving. Sometimes it is.
Speaker 2 (06:49):
But the implication is massive. Generative AI is set to
redefine content creation across almost every industry, writing articles, marketing, copy,
producing podcasts like this one, even crafting verse experiences. It
means creation becomes much more of a human AI collaboration,
which you know, raises interesting questions about authorship and creativity itself.
Speaker 1 (07:07):
Okay, so that covers the automation side. Now here's where
for me it gets really interesting. This idea that the
line between our physical world and the digital world is
blurring and blurring fast. It's not just about smart devices anymore,
is it. It's like the environment itself is becoming smart, reactive.
Speaker 2 (07:26):
Exactly, and connecting this to the bigger picture, these trends
aren't just about new gadgets. They represent entirely new ways
of experiencing and managing our physical and digital surroundings. It
definitely makes you question how even define reality when the
digital is so seamlessly integrated. You know, we're essentially building
intelligent layers right over the physical world, which.
Speaker 1 (07:47):
Takes us straight into AI crafted experience and extended reality. XR,
so VR and AR. They've been around mainly for games
or specific industries, but this sounds different. Intelligent self generating.
Speaker 2 (07:58):
Spaces, Yeah, moving beyond just a visual display. The ideas
that XR spaces won't just be static environments you visit,
they'll generate themselves, adapt based on what you do, who
you are, creating these incredibly dynamic interactions. How wod that
actually work well in videos? Already creating real time characters
in XR that can hold full, unscripted conversations, they feel
(08:18):
incredibly real. META is investing heavily in avatars that don't
just look good, but react, emote, improvise, making digital interactions
feel much more human, like.
Speaker 1 (08:29):
They understand social cues something like that.
Speaker 2 (08:32):
And think about the virtual shops shown at cees. They
could change their layout in real time based on how
people moved around inside them. The implication is much more immersive, dynamic,
personalized digital experiences that adapt instantly to you. It's moving
from just being there to the space being with you.
Speaker 1 (08:49):
And if virtual spaces are getting smarter, so are physical ones. Right,
let's talk about smart infrastructure and IoT two point zero.
This isn't just my smart thermostatus. We're talking city wide
intelligence exactly.
Speaker 2 (09:00):
It's a massive expansion. Think beyond individual gadgets to interconnected
devices creating intelligent, self optimizing physical environments on a huge scale.
The prediction is staggering over thirty billion IoT devices globally
by twenty twenty six.
Speaker 1 (09:15):
Thirty billion. Okay, so what does that actually enable.
Speaker 2 (09:17):
We're seeing it already. Traffic lights in Singapore that adjust
in real time to congestion based on live data. It
significantly improves traffic flow.
Speaker 1 (09:26):
Right, I've heard about that.
Speaker 2 (09:27):
Or warehouses using tech from a TOWUS or Verizon for instant,
human free inventory tracking, optimizing logistics like never before. And
in South Korea they have these smart poles doing multiple things,
monitoring air quality, providing Wi Fi charging phones.
Speaker 1 (09:43):
Huh, infrastructure doing more.
Speaker 2 (09:45):
Precisely, so cities, industrial complexes become more efficient, responsive, data
driven potential for less waste, better quality of life. It's
like a foundational layer for smart living.
Speaker 1 (09:56):
This blending of digital and physical. It feels like it's
going to change how we even access information, which brings
us to AR glasses replace screens. AR glasses have felt
like they're just around the corner for years. Is this
finally it? Or are they becoming practical?
Speaker 2 (10:12):
The sources strongly suggest yes, they're reaching a point of
practical usefulness where they could genuinely reduce the need to
constantly pull out your phone.
Speaker 1 (10:19):
So what makes now different?
Speaker 2 (10:20):
Well, Apple's vision pro, while maybe bulky and expensive for now,
definitely kicked things into high gear. It showed what's possible.
Now you have Meta XR, Reel, Samsung all working hard
on lighter, more practical.
Speaker 1 (10:33):
AR glasses, and what could they do.
Speaker 2 (10:35):
Imagine real time captions appearing in your vision during a
conversation or navigation, arrows overlaid directly onto the street as you.
Speaker 1 (10:42):
Walk, or even translated subtitles floating there when someone speaks.
Speaker 2 (10:45):
Another language exactly, and the key is AI handling the context.
The glasses might anticipate what info you need before you ask.
The implication is this seamless information layer over the world,
transforming how we access digital content, making it ambient, contextual,
always there, but not intrusive, like a digital sixth sense.
Speaker 1 (11:06):
And these intelligent layers, they're coming into our homes too,
aren't they, Which is AI powered home assistance. We have
smart speakers now, but this sounds like robots in the house.
Speaker 2 (11:15):
It's definitely an evolution beyond just a voice in a box.
They're becoming mobile, versatile, more intelligent home robots, a physical
presence that can move and interact with the.
Speaker 1 (11:24):
Environment, like Rosy, the robot from the Jetsons. Are we
there yet?
Speaker 2 (11:27):
Maybe not quite Rosy, But look at Amazon's astro introduced
in twenty twenty one. It's been getting smarter. It's already
used for home patrol, elder care assistants, even delivering small
items on command in homes and offices.
Speaker 1 (11:41):
Okay, so practical uses are emerging.
Speaker 2 (11:43):
Yeah, and Apple's rumored to be working on a tabletop robot,
maybe for dynamic FaceTime calls. In China, you see humanoid
assistance in showrooms already interacting with customers. They're moving beyond
just voice. They have screens, wheels, arms, sometimes even facial expressions.
So the implication is a greater physical presence, more functional capability,
(12:03):
integrating deeper into our daily routines. They're becoming more like
active members of the household.
Speaker 1 (12:08):
Okay, so we've covered automation and the physical world getting smarter.
What does this all mean for us personally? Yeah, it
feels like tech is getting incredibly close, almost invisible, but
really impactful, especially health.
Speaker 2 (12:21):
Privacy, right, and that raises really important questions, doesn't it.
How do we navigate a world where tech understands us
so intimately, even biologically, and crucially, how do we make
sure our privacy or autonomy keeps pace. It's that balance
between incredible convenience and protecting sensitive information.
Speaker 1 (12:40):
And the first place this hits home is wearables that
know you better than you do. We've gone from step
counters to pretty sophisticated health monitors already, but this sounds
like another level entirely.
Speaker 2 (12:51):
It really is devices like or rings, whoop bands. They
already give detailed recovery scores, sleep analysis, stress metrics, actionable insights.
The emerging stuff is revolutionary non invasive blood sugar tracking.
Imagine that for diabetics, no more finger.
Speaker 1 (13:06):
Pricks that would be life changing for millions.
Speaker 2 (13:08):
Absolutely, companies like Mavena are working on continuous blood pressure wearables.
Some smart rings can even detect tiny skin temperature changes
before you feel sick, giving early warnings for illness.
Speaker 1 (13:18):
Wow, predicting illness.
Speaker 2 (13:20):
It seems like it, And the crucial part is the AI.
It's not just raw data that AI analyzes. It gives
personalized nudges predictions. Instead of just U slaped seven hours.
It might analyze months of data and suggest specific routine
changes for better recovery based on your patterns. So the
implication is the shift to proactive health management, early detection,
(13:40):
personalized wellness guidance, moving from reactive healthcare to preventative optimized.
Speaker 1 (13:45):
Well being and building right on that. Personal health data
is AI and healthcare gets personal. This sounds like AI
moving into the formal healthcare system.
Speaker 2 (13:54):
Diagnosis treatment, Yes, revolutionizing diagnosis, risk prediction and personalized treatment,
making medicine more precise proactive. The diagnostic breakthroughs are stunning.
In twenty twenty four, Google deepminds AI could spot twenty
one diseases just from retinal scans, often earlier than doctors.
Speaker 1 (14:10):
Twenty one diseases from an eye scan.
Speaker 2 (14:12):
Yeah, picking up patterns humans might miss. And hospitals in
the US are using AI to analyze patient data to
predict sepsis or cardiac risk hours before symptoms are obvious,
allowing critical early intervention. I could save so many lives definitely,
And in cancer treatment, AI is helping create personalized chemotherapy
plans based on an individual specific genetic makeup, moving way
(14:32):
beyond one size fits all. So the implication is more
accurate earlier diagnoses, proactive intervention, tailored treatments, leading to better
patient outcomes and a more efficient system.
Speaker 1 (14:42):
Okay, but with all this incredibly sensitive health data being used,
privacy becomes a massive concern, doesn't it, which leads us
to privacy first, AI and local processing? Is this about
AI doing its work on my device, not in the
cloud exactly?
Speaker 2 (14:57):
It's a really significant shifts tasks directly on your phone,
your laptop, you're wearable, driven by demands for both privacy
and speed keeping your data close.
Speaker 1 (15:06):
How is that possible? Doesn't AI need massive computing power?
Speaker 2 (15:10):
Well, the chip makers are building hardware specifically for this.
Apple's new chips, the A seventeen pro the M four.
They handle complex AI tasks right on the device, no
cloud upload needed from many things Metaslama three models can
run locally too. Intel's Meteor Lake chips have built in
AI accelerators and PUS neural processing units. Yeah, specialized circuits
for efficient AI calculations using less power and regulations like
(15:33):
GDPR in Europe CCPA in California. They're pushing development this
way too, towards offline on device processing. So the implication
is better privacy, faster processing, no cloud lag, and AI
that learns to keep your data private.
Speaker 1 (15:47):
It builds trust, and if AI is running locally efficiently,
it can become much more integrated into everything we do
on our devices. Yeah, which is AI native operating system,
So not just AI and apps, but the whole OS
becoming intelligent.
Speaker 2 (16:01):
Precisely. We see hints now like predictive text or autocorrect,
but this is deeper AI intelligence woven into the OS itself,
providing system wide help. Microsoft is testing c Pilot and
Windows eleven. You can ask your desktop to summarize files,
rewrite emails, generate images without switching apps.
Speaker 1 (16:18):
Ah, So the OS itself becomes the.
Speaker 2 (16:20):
Assistant kind of Yeah, a dynamic partner, not just a
static interface. Apple's expected to announce more AI native features
in mac os and iOS too, running on those new
neural engines. The implication your whole computer system gets smarter,
more proactive thinking with you, enhancing productivity, making interactions more intuitive,
moving from a tool you command to a partner that anticipates,
(16:42):
and this.
Speaker 1 (16:42):
Deep integration, this on device intelligence. It all depends on
the hardware, right, which is why we have jaichips everywhere.
The idea that pretty much any new device will have
a dedicated aichip.
Speaker 2 (16:53):
That's the strong trend. Yes, the next phone or laptop
you buy, chances are it'll have an AI chip built in.
This EDGAI means real time smarts right there on your device,
no cloud lag.
Speaker 1 (17:03):
So what do these chips actually enable on the device.
Speaker 2 (17:05):
Things like instant language translations, sophisticated image editing, really nuanced
voice recognition, all happening locally. Apple's A seventeen pro M
four chips do this. Qualcom Snapdragon x Elite brings it
to Windows laptops. Intel's meteor La like chips with those
MPUs handle AI efficiently even low power tasks. The implication
(17:26):
is every device becoming its own little brain. Capable of
complex AI locally enhancing speed, privacy, efficiency, making smart features
instant and personal.
Speaker 1 (17:36):
Okay, this next section, honestly it feels like it's straight
out of science fiction. Yeah, but the sources are telling
us this stuff is happening now. It's accelerating incredibly fast,
robots walking among us, machines reading thoughts. It's kind of
challenging our basic notions of what's possible.
Speaker 2 (17:51):
It really is, And what's fascinating is how quickly these
things are moving from theory or labs to actual practical application,
especially in areas people thought were still decades away. It
definitely raises big questions about our future collaboration with machines,
doesn't it. How do our rules evolve when machines become
so capable?
Speaker 1 (18:07):
Which leads us to AI enhanced robotics In retail and logistics.
We've seen factory robots, but this sounds like robots becoming
much more common and smarter in places like shops and warehouses.
Speaker 2 (18:18):
Yes, moving beyond simple, repetitive tasks to more intelligent, adaptive roles.
They're not just pre programmed anymore. We're seeing real deployments.
Agility robotics put its digit robot in Amazon warehouses in
twenty twenty four. It's bipedal designed to work alongside people.
Speaker 1 (18:36):
Walking robot in Amazon.
Speaker 2 (18:37):
Yeah, and Walmart's using autonomous shelf scanners in over one
thousand stores for real time inventory. You see those little
Starship or Kiwied delivery bots on college campuses. They're navigating
complex environments autonomously, and the key is they use AI
vision real time mapping, and they learn getting smarter over time.
Worker shortages are accelerating adoption too. They're becoming indispensable tools,
(19:00):
not just novelties. So the implication is robots becoming essential
intelligent parts of these sectors, changing operations and augmenting human work, and.
Speaker 1 (19:07):
Then taking it even further. Humanoid robots go commercial. This
is the one that really feels like sci fi. Becoming
real robots that look and move like us working.
Speaker 2 (19:18):
It's a massive step and it's happening. They're moving out
of labs into commercial settings doing practical tasks. Figure ai
partnered with BMW in twenty twenty four to put its
humanoid robot Figure one into car manufacturing.
Speaker 1 (19:31):
Wow in a car factory.
Speaker 2 (19:33):
Yes Agilities, digit is in logistics Tessel's optimis while still developing,
is already doing basic factory tasks like sorting parts, folding things.
The key is they can now walk, stably, lift things,
perform tasks with enough dexterity to be genuinely useful.
Speaker 1 (19:49):
But aren't the incredibly expensive.
Speaker 2 (19:51):
That's the other crucial factor. They're becoming economically viable. Projections
suggest some models could cost less than a small car
by twenty twenty six. That makes scaling possible, implication a
potential scalable humanoid workforce, augmenting human labor, especially for dangerous
or repetitive jobs.
Speaker 1 (20:07):
Okay, from humanoid robots to something even more out there.
Quantum computing nears utility. It's always sounded like theoretical physics
decades away. Is it actually getting close to being useful?
Speaker 2 (20:16):
The sources suggests Yes, it's rapidly approaching practical utility for specific,
very complex problems. It's moving from hypothesis to engineered reality.
IBM hit one thousand cubits in twenty twenty three, aiming
for over thirteen hundred this year. That's a huge milestone.
Speaker 1 (20:33):
Quibits, Yeah, they're the quantum equivalent of bits, right.
Speaker 2 (20:36):
Yeah, but fragile, exactly, very fragile which is why the
work on error correction is so critical. IBM and others
are making progress there, which is key to making them
reliable for real applications. And the potential uses are groundbreaking.
Simulating molecules for drug discovery at speeds impossible for classical computers,
revolutionizing medicine material science.
Speaker 1 (20:56):
Okay, so specialized high impact areas first yes.
Speaker 2 (20:59):
Or optimized incredibly complex systems like global supply chains, things
that overwhelm current supercomputers. Google, Io and q Righetti are
all racing ahead too. It's still early days for general use,
but the demos are concrete. The pace is quickening, It
hints it solving previously unsolvable problems.
Speaker 1 (21:15):
And finally, the one that pushes the boundaries, the furthest
maybe the most intimately, the rise of Brain Computer Interfaces
BCIs connecting the brain directly to computers. This isn't just
research anymore.
Speaker 2 (21:29):
No, it's decisively transitioning to real world clinical applications, enabling
direct communication, a neural bridge between brain and device, bridging
thought and digital control.
Speaker 1 (21:40):
That sounds profound, it is.
Speaker 2 (21:42):
The landmark event was early twenty twenty four, Neuralink confirmed
its first human cheap implant that person could control a
computer cursor just by thinking.
Speaker 1 (21:51):
Wow, just by thinking yeah.
Speaker 2 (21:53):
And while neuralink is invasive, other companies like synchron Precision
Neuroscience are developing less invasive methods, often aimed at restoring
function for people with paralysis, giving them back mobility or communication.
Speaker 1 (22:04):
The real medical breakthroughs are happening absolutely.
Speaker 2 (22:07):
Clinical trials have seen stroke patients regain limb control using
BCIs or send messages just through thought bypassing damaged nerves.
The implication is massive and not theoretical anymore. Bridging thought
in digital control offers huge potential for medicine for restoring
lost function, but also fundamentally redefines human computer interaction itself,
(22:28):
the ultimate interface.
Speaker 1 (22:30):
Wow. Okay, that was an incredible journey through those seventeen trends.
It really is mind boggling, isn't it to think these
aren't distant predictions, but things happening right now, unfolding around
is It almost feels like living in the sci fi story.
Speaker 2 (22:42):
It really does, and what we've covered highlights just how
pervasive these shifts are. From how we work and create
thanks to automation and AI, to how we interact with
our environment through smart infrastructure and ar, and even down
to the deeply personal our health, our privacy, maybe even
our thoughts with wearables and BCIs. These aren't just tech upgrades.
They're fundamental redefinitions of our relationship with technology and maybe
(23:04):
even with ourselves.
Speaker 1 (23:05):
And that's exactly why understanding this stuff isn't just interesting,
it feels crucial. Now. Hopefully this deep dive gave you
not just information, but real insights into the currents shaping
your daily life, your work, your wellness in the very
near future. It's about being informed, prepared, ready to navigate
this evolving landscape.
Speaker 2 (23:24):
And as technology gets better at anticipating our needs, operates
autonomously around us, even connects directly with our thoughts, it
leaves us with a really profound question to think about,
doesn't it. What does this all mean for things like
human intuition, our creativity, maybe even the definition of consciousness itself.
When our minds can start to seamlessly extend into the
(23:45):
digital realm.
Speaker 1 (23:46):
That is a powerful thought to end on. We really
hope you'll reflect on which of these trends resonated most
with you, or how you see them impacting your own life,
your community, your work in the coming couple of years,
the conversation really is just beginning.
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