Ep #95: OpenAI and Moderna, Microsoft Phi-3, Sam Altman & AI Leaders Join Homeland Security AI Board
Summary
TLDRIn this episode of the Artificial Intelligence Show, hosts Paul Roet and Mike Kaput delve into the transformative power of AI within businesses. They discuss the concept of 'AI emergent' companies, highlighting case studies of firms like Mna and Asana that are integrating AI across their operations. The hosts also touch on the importance of leadership buy-in and a clear vision for AI adoption. Additionally, they explore Microsoft's introduction of smaller language models, which could make AI more accessible for organizations with limited resources. The episode covers the formation of an AI Safety and Security Board by the US government, featuring tech and business leaders, and the potential implications for AI infrastructure. They also discuss the rapid advancements in AI technology, as exemplified by comments from Sam Altman, OpenAI's CEO, on the iterative deployment and continuous improvement of AI models. The show concludes with updates on AI in wearables, the competitive landscape for AI coding assistants, and the strategic embedding of AI across HubSpot's product suite.
Takeaways
- 🚀 Companies aiming to integrate AI effectively require support from top executives and a visionary leader with a clear plan to transform the organization over the next three to five years.
- 📈 AI adoption is seen across enterprises like madna and Asana, where employees are empowered to find AI applications for their specific roles, leading to innovative use cases and increased efficiency.
- 🌟 AI emergent companies are established organizations that quickly adopt and scale AI across all areas, with visionary leadership and a commitment to building a smarter business through AI and machine learning.
- 📊 Madna's case study shows a successful deployment of AI with 750 custom GPTs created within two months of adopting OpenAI's technology, highlighting the potential for AI to accelerate business processes.
- 🔍 Asana's integration of AI into operations demonstrates a product-first approach, with a focus on building AI literacy and hands-on experience for employees to drive a company-wide transformation.
- 🔑 Small Language Models (SLMs) from Microsoft offer many capabilities of larger models but with reduced size and data training requirements, making AI more accessible for organizations with limited resources.
- 🛡️ An AI Safety and Security Board, including tech and business leaders, will advise the US Department of Homeland Security on safely deploying AI within critical national infrastructure.
- 📱 Meta is enhancing its Ray-Ban smart glasses with new styles and more powerful AI, allowing users to interact with AI through voice commands and access real-time information.
- 💡 The launch of a new AI startup, backed by former Google CEO Eric Schmidt, aims to challenge GitHub Copilot with an advanced AI coding assistant, reflecting growing interest in AI for software development.
- 🤖 Elon Musk's AI company, Neuralink, is reportedly close to raising significant funds, which may be used to train advanced generations of its AI, indicating continued investment in AI's potential for robotics and beyond.
- 📲 Apple's discussions with OpenAI and Google suggest that the tech giant is considering integrating third-party AI technologies into its iPhone features, indicating a strategic approach to leveraging various AI capabilities.
Q & A
What is the significance of having a leader with a vision for AI transformation in a company?
-A leader with a clear vision for AI transformation is crucial as they can drive the organization to adopt AI across all areas, ensuring that the company innovates faster, excels at personalization, and can withstand competition from AI-native companies.
Why is it important for companies to have support from the top for AI initiatives?
-Support from the top ensures that AI initiatives are aligned with the company's strategic goals, have the necessary resources, and can be effectively implemented across different departments, leading to a more unified and successful transformation.
What does the term 'AI emergent companies' refer to?
-AI emergent companies are established organizations that quickly adopt and scale AI across all areas of the business. They are led by visionary leaders who invest in AI capabilities to build a smarter business and have expanding AI and machine learning talent pools.
How does the adoption of AI change the dynamics of a company's operations?
-AI adoption can lead to more efficient and effective operations by automating repetitive tasks, providing predictive models for revenue growth, and unlocking new creative possibilities. It can also enable personalized marketing, sales, and services, enhancing customer experiences.
What are some of the challenges faced by companies when adopting AI on a large scale?
-Challenges include building a workforce that is literate in AI, managing cultural changes, providing the necessary training, and ensuring that AI tools are properly integrated into existing workflows without disrupting business operations.
Why is it essential for companies to train their employees on AI tools?
-Training employees on AI tools is essential to ensure that they can effectively use these tools to enhance their work. Without proper training, the AI tools may not deliver the expected impact, and the company's investment in AI may not yield the desired results.
What is the role of small language models (SLMs) in making AI more accessible to organizations?
-Small language models offer many capabilities of larger models but require less computational power and can run on smaller datasets. This makes them more accessible to organizations with limited resources and can be fine-tuned more easily for specific tasks.
How can small language models potentially streamline AI adoption for organizations?
-Small language models can perform well on simpler tasks, reducing the need for costly and complex large models. They can be more easily integrated into existing systems and can run locally on devices, making AI adoption more feasible for a wider range of organizations.
What are the potential benefits of having AI models that can run on devices without an internet connection?
-The ability to run AI models on devices without an internet connection can lead to more reliable and faster performance, as there is no dependency on cloud connectivity. It can also enhance privacy and security by keeping data local.
Why is it important for AI models to be fine-tuned for specific scenarios?
-Fine-tuning AI models for specific scenarios allows them to perform better and more reliably by using high-quality, handpicked data sources. This customization can lead to improved accuracy and effectiveness in tackling particular tasks or problems.
What is the significance of the AI Safety and Security Board being formed by the US government?
-The AI Safety and Security Board will advise the Department of Homeland Security on the safe deployment of AI within critical national infrastructure. This includes making recommendations on protecting systems against AI threats and ensuring the security and reliability of infrastructure.
Outlines
🚀 Transformative AI Leadership and Organizational Support
The first paragraph emphasizes the importance of leadership and organizational support for the successful integration of AI. It discusses the need for a visionary leader with a clear plan to transform the company over the next five years, highlighting a three-to-five-year window of opportunity for industries to adapt to AI. The discussion is set within the context of the 'Artificial Intelligence Show' podcast, hosted by Paul Roet and Mike Kaput, who delve into AI news, its implications for businesses, and the importance of AI literacy.
🌟 AI Emergence in Business: Case Studies and Strategies
The second paragraph explores the concept of AI Emergence, where established companies reinvent their businesses with AI. It details case studies from MNA and Asana, showcasing how these companies have integrated AI across various business functions, empowering employees to innovate and build AI tools for their roles. The paragraph underscores the commitment to AI, the importance of identifying high-value AI use cases, and the role of leadership in fostering a culture of AI adoption and continuous improvement.
📈 MADNA's AI Integration and the Impact of Generative AI
The third paragraph focuses on MADNA's aggressive adoption of generative AI, aiming for 100% proficiency within six months. It outlines the company's strategic approach, including change management initiatives, training programs, and the engagement of the CEO and executive committees. The case study illustrates MADNA's belief in the transformative power of AI, with the potential to perform tasks that would otherwise require a significantly larger workforce.
🤖 AI Transformation vs. Tool Use: Emphasizing the Learning Curve
The fourth paragraph discusses the necessity of viewing AI as a transformative tool rather than just another tool to be used. It stresses the importance of investing time in learning and experimenting with AI tools to achieve desired outcomes. The paragraph also mentions the different approaches taken by MADNA and Asana, highlighting the importance of top-down support and a company-wide commitment to AI integration.
📱 Small Language Models (SLMs): Microsoft's AI Innovation
The fifth paragraph introduces Microsoft's new family of Small Language Models (SLMs), which offer similar capabilities to larger models but with reduced size and data training requirements. It discusses the potential of SLMs to make AI more accessible and cost-effective for organizations, allowing them to run locally on devices like smartphones. The paragraph also touches on the future of AI adoption, suggesting a shift towards a portfolio of models tailored to specific needs.
🏛️ AI Safety and Security Board: US Government Initiative
The sixth paragraph covers the formation of an AI Safety and Security Board by the US government, which includes CEOs from major tech companies. The board's purpose is to advise on the safe deployment of AI within critical national infrastructure. The paragraph also notes the absence of certain tech leaders and discusses the importance of having a diverse group of experts to address the complexities of integrating AI into infrastructure.
🛠️ AI Infrastructure Challenges: TSMC's Arizona Plant
The seventh paragraph delves into the challenges faced by TSMC, a leading AI chip manufacturer, in building and staffing a chip fabrication plant in Arizona. It highlights cultural and operational obstacles, emphasizing the difficulties of replicating TSMC's success in other regions.
Mindmap
Keywords
💡AI Emergent Companies
💡Generative AI
💡AI Adoption
💡AI Literacy
💡Small Language Models (SLMs)
💡AI Safety and Security Board
💡AI Native Companies
💡AI Transformation
💡AI Policies and Principles
💡AI and Infrastructure
💡AI in Wearables
Highlights
The importance of having support from leadership for AI initiatives and a visionary leader to transform the organization over the next five years.
The concept of 'AI emergent' companies, which are established organizations that quickly adopt and scale AI across all areas of the business.
MDNA's partnership with Open AI to deploy Chat GPT Enterprise, resulting in 750 custom GPTs created within two months of adoption.
Asana's integration of AI into every aspect of their operations, empowering employees to find their own use cases and build tools for specific roles and needs.
The necessity for organizations to view AI adoption as a transformation, not just tool use, and to invest time and resources into training and infrastructure.
Microsoft's announcement of the F3, a family of small language models (SLMs) that offer capabilities similar to large models but with reduced compute requirements.
The potential for small language models to increase AI accessibility and adoption for organizations with limited resources.
The formation of an AI Safety and Security Board by the US government, which will advise on the safe deployment of AI within critical national infrastructure.
The absence of notable figures like Elon Musk and Mark Zuckerberg from the AI Safety and Security Board, indicating a focus on infrastructure and less on AI expertise.
Sam Altman's comments on the iterative deployment of AI models, emphasizing that current models like GPT-4 are the least capable AI we will ever use.
Challenges faced by TSMC in building and staffing a chip fabrication plant in Arizona, highlighting cultural and technical obstacles in AI infrastructure development.
Meta's expansion of its Ray-Ban smart glasses collection with new styles and more powerful AI, allowing for real-time information access and multimodal AI updates.
The emergence of a new AI startup, Augment, backed by former Google CEO Eric Schmidt, aiming to challenge GitHub Copilot with an advanced AI coding assistant.
Elon Musk's AI company, Neuralink, reportedly close to raising $6 billion for the development of its AI assistant, Grok, with a focus on training powerful models.
Apple's discussions with OpenAI about using its AI to power new iPhone features, indicating potential integration of advanced AI capabilities into iOS 18.
HubSpot's unveiling of new AI features across its hub products, including video generation from text, AI-powered reply systems, and predictive AI for sales forecasting.
Transcripts
you can be building your ad counselors
you can be trying to lead within your
department but the companies that
probably win here it's going to come
from the cite you're going to have
support from on high and you're going to
have a a leader who has a vision to
transform the organization over the next
five years because I think that's
probably the the window of opportunity
for most Industries is you got three to
five years to figure this out
basically welcome to the artificial
intelligence show the podcast that helps
your business grow smarter by making AI
approachable and actionable my name is
Paul rer I'm the founder and CEO of
marketing AI Institute and I'm your host
each week I'm joined by my co-host and
marketing AI Institute Chief content
officer Mike kaput as we break down all
the AI news that matters and give you
insights and perspectives that you can
use to advance your company and your
career join us as we accelerate AI
Literacy for all
[Music]
welcome to episode 95 of the artificial
intelligence show I'm your host Paul rer
along with my co-host Mike put we are
coming to you early this week it is 7:20
a.m. eastern time on Monday April 29th
in our world so uh yeah always the
disclaimer of anything crazy happens on
Monday that doesn't make the show that
is why um so you know it it's
interesting week like it didn't seem
like a crazy news week not a lot of
breaking stuff no make you know major
new tech emerging that we saw know major
funding announcements and yet there's
some really fascinating topics to cover
that I think continue to sort of set the
stage about where we are and where we're
going both in terms of like regulations
some evolving models and um you know the
first big thing we'll talk about today
Mike is the you know a couple of
examples of these AI emergent companies
and I think this is the kind of stuff
like I've been anxious to be able to get
to on the podcast like the real
applications of comp companies that are
actually doing this the right way like
full-blown adoption across the
Enterprise so uh again like no major
breaking news yet something happens
while we're talking here but uh I think
some really valuable stuff for people
today um that can help you along your
your path so today's episode is brought
to us again by rosa. rosa. is the
ultimate game changer for AI powered
newsletters rosa. smart newsletter
platform tailor your news newsletter
content for each and every subscriber
and automates tedious newsletter
production tasks we've known the team at
rosa. for years now uh and think their
solution is well worth checking out join
the 500 plus organizations leveraging
rosa. and get a personalized demo today
at rosa.
maaii um and again I I've mentioned this
on one of the previous read throughs on
rosa. but like Mike and I use it as an
internal newsletter so um we don't run
our Institute newsletter through it but
we actually find it helpful just for
internal research purposes because it'll
send us you know links to look at and
things like that so it's one of the
sources that we use to actually Cate The
Weekly News so um just another potential
use case you can think about for smart
newsletters like that um and then the
second is uh we've been mentioning this
our 2024 state of marketing AI survey is
in the field now you can be a part of
that research this is the what did we
said Mike fourth year this is actually
year four I think I misspoke on the last
episode yeah okay so year four of This
research so we've got fascinating
research going back uh four years now
where we take a deep dive into what is
actually going on in uh artificial
intelligence within the marketing
industry look at use cases uh you know
how people are thinking about it
obstacles for adoption within Enterprise
we're asking questions this year around
um do you have generative AI policies do
you have responsible AI principles like
really trying to get deeply into the the
understanding of where the market is
right now with AI adoption so we'd be
appreciative if you have a few minutes
and can be a part of that survey it is
State ofmarketing
a.com uh you can go there you can
download the 20123 report and click the
link at the top that says 2024 survey
and be a part of that research we will
be releasing that in summer of 2024 so
coming up in a few months so again state
ofmarketing ai.com to be a part of that
research all right Mike it's all you all
right Paul so you alluded to our first
big topic today which is we're seeing a
couple new case studies come out that
detail companies becoming what we would
call AI emergent or these are existing
firms that are Reinventing their
businesses with AI the first case study
details a partnership between Mna and
open AI to deploy chat GPT Enterprise to
thousands of employees across that
company according to open AI quote now
every function is empowered with AI
creating novel use cases and gpts that
accelerate and expand the impact of
every team at the company they also say
that within 2 months of chat GPT
Enterprise adoption madna had
750 custom gpts they had created across
the company 40% of weekly active users
were creating gpts and each user had on
average 120 chat GPT conversations per
week now within madna this is happening
across literally hundreds of possible
use cases across the business they've
got a GPT to review clinical data using
some of the data analysis capabilities
that chat GPT has they have gpts that
their legal team uses to summarize
contracts and they have gpts that help
employees get quick answers about
internal policies at the company now as
we heard this we also got an article
that contained a detailed breakdown from
assana co-founder and CEO Dustin Dustin
moscovitz how the about how the company
evolved to integrate AI into every
aspect of their operations that included
building Bots for feedback for reviews
for sales and customer experience and
for Content creation so it sounds like
Asana also took this kind of similar
approach to madna despite them being
very different types of companies in the
sense that they empowered employees to
go find their own use cases and build
their own tools for their specific roles
and needs moscovitz even details how
everyone from sdrs to product marketers
to HR professionals were able to
actually identify high value AI use
cases in the company and build AI tools
themselves to support their work and he
noted multiple times they often didn't
really have significant technical
backgrounds so Paul this caught our
attention for a few reasons but first up
can you kind of maybe talk a little bit
more about what we mean when we say AI
emerging companies and why it's so
important to be looking at these types
of case studies yeah I was so excited to
see this case study I mean I get like
there it's a case study from open AI
it's going to be obviously very
favorable certainly you know adoption in
Enterprises isn't this seamless but you
know the whole point here is just to see
the depth of commitment that was made to
to to integrate Ai and I think it's a
great representation of what
organizations should be thinking about
and pursuing so going back to the AI
emerging concept so I wrote a blog post
we'll link to it in the notes and I had
to go back and look when I wrote this it
was May 16th
20122 so set the stage to may may 2022
mid Journey was a couple months old we
had Dolly had been previewed I don't
think it was readily available yet um
Mike and I were finishing the manuscript
for our book so our book came out in
summer of 22 the artificial marketing
artificial intelligence book um and we
were uh what about seven months prior to
chat gbt being introduced so that's kind
of the stage we were at but we were
already seeing at that point the
inflection point was arriving in our
opinion as to like we really were going
to have this future whereas I wrote you
were going to be AI or obsolete um and
so I'll just like pull a few excerpts
from that post post because I think it's
very relevant and what we're now seeing
is kind of these companies we envisioned
are now coming to life so in that post I
wrote with each day that passes and each
advancement in artificial intelligence
language and vision technology is
becoming more apparent that there will
be three types of businesses in every
industry AI native AI emergent and
obsolete um I keep running through
examples in my mind I said retailers
e-commerce shops marketing agencies
media companies law firms medical
practices keep going and I can't can't
come up with an industry or business
model where this won't be true I went on
to write take any of these or your own
business and simply look for
inefficiencies and repetitive processes
opportunities to drive Revenue through
greater predictive models such as uh
customer acquisition retention and
growth and ways to unlock ideation and
Innovation through previously
unattainable creative possibilities you
could later add degenerative
capabilities to that as those became
readily available to people and then in
that post we went on to describe AI
emergent company as established
organizations that move quickly to adopt
and scale AI across all areas of the
organization they have Visionary leaders
who see the rapid advancements in AI
capabilities and invest the resources
needed to build a smarter business these
emergent companies have expanding Ai and
machine learning Talent pools um and at
the time I referenced Adobe for example
had 300 AI ml employees at that time
according to LinkedIn they innovate
faster than the competition potentially
through Venture Studios or R&D Labs on
building aite Tech and they excel at
personalization across Marketing sales
and service they have the data customer
bases and infrastructures to withstand
the AI native companies so the startups
that are building AI first if they move
fast enough to transform plus they have
the money to acquire the AI native
companies before they grow to dominate
so that just sort of sets the stage of
like going back to 2022 how we were
looking at uh sort of the future of
business then you fast forward to today
with this madna example and the thing I
love about I mean I don't know who I
don't know if gp4 wrote the the case
study but it's a really well done case
study Mike and I used to write case
studies and things like this for clients
back in our you know agency days this is
really well done because what I loved is
they LED with the why so it said madna
is using its platform for developing
mRNA medicines to bring up to 15 new
products to Market in the next 5 years
in order to achieve its Ambitions madna
has ad oped a people Centric technology
forward approach constantly testing new
technology and Innovation uh that can
increase human capacity in clinical
trials so they they basically kind of
lay out the fact that they're having
this um unparalleled growth opportunity
and at one point they actually literally
say that this would take uh thousands of
people to do if they weren't using AI so
the the CEO as quot says we believe very
profoundly at madna the Chad GPT and
what open ey is doing is going to change
the world we're looking at every
business process and this part I love
from legal to research to manufacturing
to Commercial and thinking about how to
redesign them all so this is like again
go back to thei merging definition it's
a it's a Visionary leader like you need
someone who's looking at his head saying
this isn't just like a marketing thing
this isn't every function of the
organization thing and we're going to
like aggressively push this then it went
on to say that their um their objective
was to achieve 100% of adoption and
proficiency of generative AI by all its
people with access to digital Solutions
within 6 months quote we believe in
collective intelligence when it comes to
Paradigm changes it's everyone together
everyone with a voice and no one left
behind then they said they had
individual change man management
initiatives including in-depth research
and listening programs as well as
trainings hosted iners online and with
dedicated AI learning companions um they
had prompt writing competitions to find
the top 100 AI power users they had
local uh office hours with every
business line in geography with over
2,000 actly week participants um
structured change management initiatives
including engaging madna CEO and
executive committees and then there was
a quote in here from their Chief
Information officer Brad Miller um said
90% of companies want to do gen but only
10% of them are successful and the
reason they fail is because they haven't
built the mechanisms of actually
transforming the workforce to adopt new
technology and new capabilities this is
exactly what we've been saying Mike like
that like people complain that it
doesn't have the impact it should have
and the models aren't smart enough or
they make mistakes and the thing we
always say is you're not thinking about
this the right way you're not properly
training everyone like you can't just
buy the tool give it to everyone and a
think it's just going to happen so they
went on to say you cited a couple of
those metrics but um they said within
two months they had 750 gpts 40% of
weekly active users had created a GPT
and each user had 120 chat gbt
Enterprise conversations per week on
average um and then there was a section
the the final section I want to call out
is this idea that said a team of a few
thousand can perform like a team of a
100,000 and this is where the quote came
from said if we um with an ambitious
plan to launch multiple products in the
next few years madna AI as a key
component to their success quote if we
had to do it the old biopharmaceutical
ways we might need a 100,000 people
today we really believe we can maximize
our impact on patients with a few
thousand people using technology and AI
to scale the company so I did you I
don't know if anything else caught your
attention mik but this is like again the
thing I keep saying and keep thinking
when we talk to these big Enterprises is
like you you this goes everywhere it's
every function of the business and you
have to be educating people first and
foremost and then you have to give them
like the resources to actually explore
what's possible with this technology
then encourage all the sharing so I just
I love everything about what they
feature in this case study yeah like you
like you mentioned obviously it's never
as seamless as it appears just operating
on a single case study but I think
people would be wise to look at just
look at the numbers again look at how
many conversations your average employee
is having if you are
coming away dissatisfied from these
tools because you had three or four
conversations and it didn't cut it
they're having 120 per week it's going
to take hundreds of conversations to
even begin to get towards what you want
is that kind of what you took away from
this in terms of not only the education
piece but people do need to actually
invest a large amount of time and trial
and error to get these tools to work
well yeah it's viewing it as
transformation not just tool use you I
think that's the companies that go and
saying we believe this is going to
transform our our Workforce our
strategies our our um you know our
technology stack and we're going to
approach it as such we're going to put
the right resources we're going to build
the right infrastructure put the right
governance in place like not just go get
five tools to be testing and and hope
people figure out how to get some value
out of the $30 a month license that
they're using so yeah I think it's just
the organizations that take that
approach and then you mentioned assana
it is a different approach because
they're coming at it most likely from a
product first standpoint a is a project
management system platform if you're not
familiar um we're big fans we've been
using it since I don't know we started
using her for uh the agency so probably
a decade or so been using Asana um we
use it to run the Institute from a
project management perspective um so
Dustin mosovich who you mentioned if
people aren't familiar he was actually
one of the co-founders of Facebook and
then he left and found at ass sa in 2018
he you may see his news his name in the
news otherwise because he's currently
has beef with Elon Musk
um I will I will not disclose like go
check elon's Twitter thread from Friday
I was messaging Mike when I was sitting
at dinner I was like what what happened
what did I miss I was in a talk at Ohio
University Friday afternoon and Elon
Musk put this really inappropriate tweet
up about Dustin and I was like what what
happened and Mike's like man I got no
idea so I found out what happened um
there's been a lot of beef emerging
between the two but basically he he he
said uh Tesla is the next Enron that
that it's a the whole thing is a big
scam and Elon is basically just like
selling this Future Vision of full self-
driving that's never going to happen and
so he basically just called Elon out and
said it was Enron so Elon was not very
happy with that so Dustin and news for
other reasons you may hear about um but
back to assana so the way they're
approaching it similar thing you have a
CEO with a vision for how this is going
to transform the company so they're
looking at it from a product perspect
perspective but the thing I liked about
this example is it was a letter from
Dustin so it was very clear that this is
coming from the top um and they're a
company that has been investing in AI
for a long time like we've talked about
this before AI isn't new like Chad GPT
wasn't the beginning of AI there were
companies like Assa like Salesforce like
Adobe that had hundreds of AI and ml
Engineers way before chbt emerged but
they were working on machine learning
they were working on predictive models
they were making sure predictions about
outcomes and behaviors that could be
applied to like forecasting models and
recommendation engines and um
optimization of pricing and like things
like that and products well what they're
doing now is he's saying like Okay we
were already in AI but now we're really
in and like we're really seeing the
potential of gener AI not just within
our product but within our own company
and so there was one point he said
internally reactions to AI range from
exhilaration to skepticism we knew we
needed to build literacy and hands-on
experience to unite every around this
transformation again transformation not
just tools so we launched an internal AI
community and immersive workshops
encouraging all employees to Tinker with
the technology we stood up stack slack
channels we started evangelizing the
power of AI through new internal use
cases and stories of our personal
breakthroughs that company all hands and
in team meetings and then it just goes
on to say kind of how they got everyone
involved and they began to glimpse of
future where AI moves Beyond isolated
chats to embedded contextual
collaboration kind of their own use
within this
so definitely another one to just keep
an eye on they do say they have a work
Innovation Summit on June 5th that we'll
track um where they said quote we be
showcasing in the future of human AI
teamwork and then he ends with together
let's build a future where every team
has the power of AI at their fingertips
where human creativity and machine
intelligence combined to solve The
World's Greatest challenges and where
work is not just more efficient but more
fulfilling more impactful and more
profoundly human that is like something
I would have like that is exactly what
we've been saying all these years more
intelligent more human is the tagline
we've been using um so I I love the
vision I love what they're trying to do
um we're not using any of the AI
features with venisa to my knowledge
today so you know I think we need to
probably dive back in and see if there's
anything going on um yeah but certainly
you know two good examples today of just
this whole vision of you got to have
it's got to come from the top like you
can be building your ad counselors you
can be trying to lead within your
department
but the companies that probably win here
it's going to come from the seite you're
going to have support from on high and
you're going to have a a leader who has
a vision to transform the organization
over the next five years because I think
that's probably the the window of
opportunity for most Industries is you
got three to five years to figure this
out
basically so in our next big topic today
Microsoft has announced the F3
ph-3 family of open models and these are
noteworthy because they're actually
small language models or slms according
to Microsoft slm's quote offer many of
the same capabilities found in large
language models but are smaller in size
and are trained on smaller amounts of
data now because these models are much
smaller than llms they consume far less
compute and they can run locally or have
the potential to on devices like an
iPhone so one of the main models in the
family
5-3 mini has 3.8 billion parameters it
was trained on 3.3 trillion tokens and
Microsoft says it performs better than
models twice in size there are some
other 53 models coming soon uh with more
parameters 7 billion and 14 billion have
been mentioned by Microsoft and while
large language models are basically
unmatched right now for complex tasks
and the most advanced use cases the
reason this is kind of a big deal is
that these small language models can
perform really well on a lot of simpler
things that can make AI more accessible
and easier to use for organizations with
limited resources small language models
can also be more easily
fine-tuned uh senali yav who Microsoft's
principal product manager for generative
AI said the following about this trend
quote what we're going to start to see
is not a shift from large to small but a
shift from a singular category of models
to a portfolio of models where customers
get the ability to make a decision on
what is the best model for their
scenario so Paul I found this trend
really interesting in terms of what it
could mean for AI adoption like how do
you see small language models
potentially increasing or streamlining
how organizations actually adopt
AI for just some macr level context here
again the reason why these models are
important is because it costs a lot of
money to run the big models so you know
we're building GPT 4 GPT 5 or Gemini 1.5
or you know Claude 3 Opus like the
biggest Frontier models to use those
models so training them costs hundreds
of millions or billions of dollars
that's one thing but then the inference
cost so when you and I go to use the
tool um for whatever it is to write our
email or to generate our images or
eventually to generate our you know
10-second videos that's the inference
cost so if you're using these massive
models every time you need to do a
discrete task it can get insanely
expensive so for Microsoft who's
licensing open ai's technology to do say
365 co-pilot it's built on open ai's gbt
4 4.5 whatever it is technology it costs
them a bunch of money to pay open AI to
to use it every time you or I go in and
use co-pilot so there's a lot of
motivation to build these smaller models
that don't cost as much money and what
the research seems to be showing
recently is as you alluded to you can
train these things a little easier
there's been a number of research
reports just in the last few weeks that
shows that the quality of data matters a
lot and that if you can take a smaller
model that costs less to train and costs
less to run and you can give it more
kind of handpicked data sources that
these things can perform like a much
larger model in terms of their quality
and re and reliability if the data is
really good that goes into them um Apple
actually has released a number of
research papers showing this is the
direction they're going where you build
these smaller models that don't cost as
much to run don't cost as much to train
and they can run on device so you don't
have to go to the cloud every time you
want to do something so again every time
you or I go to chat gbt or perplexity or
whatever we're going and pulling from
compute in the cloud somewhere which
costs money what they're saying is in
the future you're you could be on your
device on do not disturb or or airplane
mode and you could be running a model
doing something on your phone that's
what this means and so that's why you're
going to hear a lot more about this as
we lead into the June developer
conference for Apple um this on device
models that can do things for you on
your phone without an internet
connection is going to be a really big
unlock and I think it will lead to a lot
more adoption and it's probably going to
be much more like the adoption we had in
the 201 to 2020 range where we were all
using AI in Netflix and Spotify and
YouTube and Facebook like AI was part of
our lives and we didn't realize it
that's what this will enable is like
that these models can just be underlying
functions on your phone and you don't
even know you're using AI it's not like
you're going to a AI app to use AI it's
just going to be embedded within
everything
so in our third big topic today we got
news that Sam Alman Microsoft CEO Sachi
Adella and alphabet CEO synar pachai are
joining something called an AI Safety
and Security Board that's being run by
the US government now this board is
going to advise the Department of
Homeland Security on how it can safely
deploy AI within critical National
infrastructure so it's going to do
things like make recommendations on how
operators of core infrastructure like
power grids for instance can protect
their systems against AI threats those
kinds of topics and advisory
recommendations now almost two dozen
political Tech and Business Leaders are
on this board so some of the other
notable names uh include nvidia's Jensen
hang anthropic CEO Dario amade the CEO
of Northrup Grumman the mayor of Seattle
who's also the chair of the us
Conference of Mayors Tech and Innovation
committee the governor of Maryland and
noted AI researcher fay F Lee now Paul
when we talked about this before the
episode you mentioned that some there
were some notable omissions from this
group that stood out to you who who was
that yeah so I mean the obvious thing is
meta is not on there so no Zuckerberg no
Yan laon uh I you could say Elon Musk um
who's certainly in investing a lot to
build AI so there was some obvious ones
there and then the biggest one that
initially jumped out to me is what were
the open source people like so a lot of
the the people on here from the AI
perspective are are you know not the big
ones pushing for open- Source
acceleration um so that seemed to be U
one thing there was I did see a tweet
from Gavin Baker who you know I follow
pretty closely uh he's a managing
partner and CIO at an investment firm um
but heavily involved in AI and he
tweeted can't decide whether it is funny
ridiculous or sad that the CEOs of
ocidental petroleum and Delta Airlines
are on the new AI safety board less than
half of the 22 members have any real AI
knowledge um also odd that it's not even
vaguely bipartisan has zero open- Source
AI CEOs and excludes Elon um so that was
my initial like that was actually one of
the first times I saw this list and then
when I went back in and read about it it
actually made a lot more sense like what
his critique I think didn't necessarily
hold up at least from the business
perspective because this is all about
critical infrastructure such as the
power grid and transportation so it
makes perfect sense that someone from a
petroleum company someone from an
airline company like you would want
diversity they don't have to be AI
experts to be able to explain how
transportation in the in the United
States works or how the the energy grid
Works things like that so it's actually
smart to have a diverse group of people
that caning bring that kind of knowledge
to the table that doesn't mean that
there shouldn't be open source people on
there someone like a you know a
Zuckerberg shouldn't be on there but I
think they're basically probably looking
at which companies are we working with
on the infrastructure of the the US
economy and the government and then what
businesses are represented that need to
be there so yeah I mean My overall take
was um I I think it's good that these
conversations are happening the
infrastructure is something we don't
talk about on this show much we probably
will more it is a major problem um there
are lots of things that can go wrong
with the infrastructure and in many
cases the infrastructure is 70 years old
or more and that's a problem and it's an
attack Vector for people to use um so
yeah and then the other thing we'll come
back to this later on but there was a uh
there's a new bill um
sb147 in California safe and secure
Innovation for Frontier intelligence
models act that is uh apparently moving
pretty quickly in California and this
seems to be a bit of an attack on the
open- source world as well at least it's
being positioned by some open source
Advocates as such um Jeremy Howard who
is someone to follow on Twitter um is uh
posted an article about like his
thoughts on this so he's an AI
researcher and entrepreneur CEO of
answer. um and so he goes on as to kind
of like do a Tak down of why open source
is so important so I think again we'll
kind of come back to this maybe next
week I think it's worth talking a little
bit more about this battle between open
source and closed source as we start
moving into regulations um but it's
going to be a really important uh topic
as as we move forward especially as we
start getting into the elections and as
the government starts looking at ways to
um you know protect infrastructure and
things like that so yeah really critical
topics uh keep an eye on SP 1047 in
California it seems like it's moving
real
fast all right so let's dive into some
rapid fire topics this week the first up
is a pretty interesting public comment
from Sam Alman he recently made a public
appearance at Stanford's entrepreneurial
thought leaders seminar called ETL uh
and he had some harsh words to say about
chat gbt at one point in the discussion
he said quote chat PT is mildly
embarrassing at best gp4 is the dumbest
model any of you will ever have to use
again by a lot but it's important to
ship early and often and we believe in
iterative deployment now Paul this isn't
some groundbreaking secret knowledge
interview that he's dropping here but it
it was something I wanted to highlight
because I think many people who are
relatively new to AI don't always grasp
just how much leaders like Alman believe
existing AI technology is going to
improve and soon and you also mention
this point in your talks all the time
saying this is the least capable AI
you'll ever use could you kind of unpack
this idea a little more for us yeah you
know I think it's it is just a good
reinforcement that you know people look
at gp4 today and maybe they are
disillusioned maybe there are some
organizations or some leaders out there
who just don't see the real potential
for transformation they're not doing
what madna or assana are doing and
they're not you know really driving
because they just don't see the value so
one I think it's a really good reminder
that it's only going to get better from
here and it's probably going to get
significantly better from here and the
other thing that I thought he gave some
good perspective on is he said this in
many many interviews that it's better
that they don't just go build so they
again their mission is artificial
general intelligence AI that is at or
above human level at all cognitive tasks
generally speaking um and so his feeling
is like we don't we don't want to just
go away and build AGI and then just drop
it on the world in you know 2 years 5
years whatever and then all of a sudden
it's like oh oh my God like where did
this come from like they if we had never
seen chap chbt if we'd never experienced
these tools as they were evolving so
open AI does iterative deployment so
they're a big believer in let's ship
this stuff early ship it often and give
people a chance to react to it now if we
rewind back to I think it was gpt2 when
it first came out they put out a paper
said hey we're not releasing this into
the world because it it might be too
dangerous so they were worried about
gbt2 being misused um now people are
worried about gbt and oh my gosh what's
going to happen to society and so Sam's
whole point is like listen there's this
initial shock when when new things come
out like Chad GPT comes out everyone
freaks out and so then he said GPT 4
which came out a year ago was met with
two weeks of freaking out and people
believed it was this crazy thing and the
world had changed forever now people are
like oh it's horrible where is gbt 5 so
his whole point is like as a species we
adapt change is weird um I've referenced
the one that Andre karpathy said at one
point where he was talking about like
whmo like most people don't realize like
self-driving is actually a thing like
there are taxies basically in California
that don't have drivers and you can
order them on your phone and you can get
in them well the first time you see that
you're just like what is that and then
you continue walking down the street
like you go about your life and so I
think like as much as AI is going to
transform everything like it's going to
be this process where things just start
to be weird and you're going to look
back two years be like oh my God I can't
believe gbd4 was like what we were using
that was such a terrible tool um but
right now it feels very impactful and so
I think that's the the path we're on
with this technology but Sam's Point is
listen we we'll keep figuring it out now
I don't necessarily buy into this when
it comes to like the jobs and the
workforce and the economy conversation
which is a whole another topic um but
this is the approach of most of these
technology leaders is like hey we adapt
we figure things out it'll all be okay
and like we'll have time to solve this
so yeah that was that was the uh there
was a a few quote worthy things from the
interview at Stanford for sure it
certainly sounds like he does not think
progress on AI will be slowing down any
time no he does not yeah and he's been
very clear that the leap to five is
going to be massive uh um but yeah we we
will see hopefully well I don't know
hopefully but we'll probably see sooner
than later
see all right another topic on the
docket this week we got a new in-depth
report from a publication called rest of
world and it details some really
significant challenges that are being
seen building out AI infrastructure in
the US the article does a deep dive into
tsmc the Taiwan semiconductor
manufacturing company this is one of the
top AI chip makers on the planet that
makes AI Hardware basically possible and
it's currently engaged in efforts to
build and staff a chip fabrication plant
in Arizona so this plant has right now
about 2200 employees it's kind of seen
as this leading indicator of efforts to
diversify AI chip manufacturing away
from Taiwan just given the geopolitics
of that region and kind of great power
competition between the US and China but
this appears to be a lot easier said
than done because this report which is
well worth a read um details tons of
obstacles that tsmc is running into
trying to get this plant up and running
and primary among these aren't just you
know technical hurdles there's serious
cultural clashes between American and
Taiwanese ways of working the report
details how Americans had to go train at
tsmc and iwan for like a year but all of
the training were in Taiwanese and
Mandarin Chinese so they were basically
hacking it together with Google
Translate to learn what they were
supposed to learn there were also some
significant clashes with tsmc's work
culture which is quote notoriously
rigorous even by Taiwanese standards and
Taiwanese Engineers were also coming to
the US and then very critical of their
American counterpart work ethic and
technical skills all of this is to say
you know Paul we hear a lot of talk from
AI leaders about the need to invest
billions or even trillions into AI
infrastructure like this in the coming
years especially in the US but it just
sounds like there's some serious human
obstacles here I mean could this type of
thing hold back AI
Innovation yeah and it's totally
predictable like so if this is an
interesting topic you one it probably
should be um just if nothing else you
understand understand the supply chain
that powers your smartphones your cars
all the AI tools that we rely on today
all the ones we rely on in the future
they are all dependent upon tsmc and the
supply chain of building these chips um
also your retirement portfolio
potentially if you invest in Nvidia um
now I did hear an interview with Jensen
Hong where he said that they are relying
on tsmc in Taiwan but of the 35,000
parts that go into each chip only eight
of them are made by tsmc so it's not
like whole chip is fabricated like in in
Taiwan but it is a critical part for
sure so this affects everyone the
article is insane like it's a long read
but it is like it's comical at times but
um also sad because it's just as you
said like I I don't know how you've
solve this like and there are the the
CEO of tsmc has basically said for years
like you can't do this in America like
this isn't going to work but I'll take
your1 billion dollar and we'll try and
try and build this in Arizona for you
and we'll see how it goes and it's
mainly a culture and and labor issue
like they're just very different in
Taiwan than in in America uh and that
becomes extremely apparent when you read
this article that it is probably more um
misaligned than you could imagine to try
and do what they do in Taiwan and in the
US um so two quick recommendations Chip
War by Chris Miller great book on the
topic and then there's an article from
Forbes by Rob TOS called the geopolitics
of AI chips will Define the future of AI
um that article is from May of 2023 and
I believe the book came out in 2023 as
well so again if you're if you're
fascinated by this thread of AI um start
with the article on Forbes from Rob TOS
great insight into it he also had a Ted
Talk on the topic I believe and then if
you want to keep going read chipboard by
Chris Miller uh
it is a fascinating topic it's one of
those like I try and not spend too much
time in because it's like I have no
control of this whatsoever and there's
times where you read this stuff you're
like oh this is going to go awh like
this is not going to work out and I feel
kind of helpless so I like it's kind of
like cyber security like I'll dip in
every once a while read about it like I
got to get out of here like I got too
many other things to worry about than
the supply chain for AI chips but it's a
fascinating
topic all right next up meta has
announced that it's expanding its
Rayband meta smart glasses collection to
include a bunch of new Styles but more
importantly new more powerful AI so we
had talked last week about meta AI the
company's intelligent assistant and now
in the US and Canada you'll be able to
use that right within your smart glasses
so you just say hey meta and you can
then prompt the assistant with voice
commands now meta AI also gives the
glasses the ability to access realtime
information information and the company
began testing a multimodal AI update so
you can actually ask your glasses about
what you're seeing now that update is
now rolling out to users in the US and
Canada so Paul it definitely seems like
meta's Rayband smart glasses could be
like an actually useful way to engage
with AI in the real world we've talked a
couple times in uh the last couple weeks
about AI wearables and that whole Trend
like how do you see these stacking up
compared with some of the other
unfortunately Rocky releases of AI
wearables uh definitely a better form
factor lot more positive Buzz regarding
these than say our our Humane AI pin or
the rabbit which we won't get into but
the rabbit if you recall we talked about
I don't know 10 episodes ago 15 episodes
ago when it was first previewed it's
this device that supposedly does AI on
it at the time I was kind of skeptical
that it was one needed and two would
work it is real bad so far so they just
started getting into the hands of people
and it is it's not I don't know if it's
as bad as the a AI pin reviews but it's
real bad um probably just because it
only cost $99 instead of $799 so people
are more like accepting of the fact that
they just wasted $200 but um the rabbit
device is not going well the rayb bands
however seem like right form factor
obviously meta has endless money to
throw at this and they seem to be being
really smart I tried to find some sales
data on these things and the only thing
I came up with was August
20123 uh at that time said they' sold
300,000 of the devices but only had
27,000 monthly active users so adoption
wasn't real High um but again it's it's
not wildly expensive product so it can
be somewhat disposable if you're a
higher income person it's like you know
throw 300 bucks at something you don't
like it it's okay um I could see these
being more heavily adopted for sure in
in the months and years ahead and I
think more people will get into this
space I would be shocked if Apple
doesn't at some point apply their Vision
Pro technology um to this and by the way
we should come back to the Vision Pro at
some point yeah uh that's not going well
either I mean awesome Tac like at least
they have good Tac but it's not being
supported like there's I have like no
new apps no new immersive experiences
like I don't know what they're doing and
apparently they just cut production like
down to 400,000 units instead of 700,000
so yeah I think there's just going to be
it's going to be a rocky go with these
um kind of immersive experiences and and
AI devices um even for the big companies
but meta seems to be on track here more
than
most so we just also got some news that
a new AI startup being backed by former
Google CEO Eric Schmidt has just emerged
from stealth with a whopping $252
million in funding this company is
called augment and it aims to challenge
GitHub co-pilot by offering a better
version of an AI coding assistant to
help programmers be more productive and
effective so essentially AI assistant
that will generate code for you help you
debug code and help you create programs
much faster now the company was actually
co-founded by an ex Microsoft developer
and a former AI research scientist at
Google they are entering however a
pretty crowded and competitive market
GitHub co-pilot has 1.3 million paying
individual customers and 50,000
Enterprise customers Amazon and Google
have their own coding assistance and
there's a ton of other startups
competing in this space as well now Paul
while we don't have a ton of details
just yet on this company it has raised a
significant amount of money has some
notable investors its Founders have
interesting and relevant backgrounds
these kind of tick all these boxes we
look for when it comes to paying
attention to certain companies like what
are your first impressions of this yeah
so we on a reev recent episode we talked
about you know what startups get our
attention um the investors the amount of
investing the founding team sort of like
check check check and and this one Eric
Schmidt if if you're not familiar he was
the CEO and chairman of Google
from1 so just a couple years after they
were founded he was sort of the adult
brought into the room basically to kind
of guide um Google and so he was the CEO
till 2011 and then he stayed on as the
chairman of the board I think until
200 what 15 or 18 um and so he's you
know a billionaire and uh he invests
heavily he advises the government and I
think the Department of Defense he's
like an adviser for AI there so he's
heavily involved uh still and so to see
him uh leading this kind of round for a
company to come out of Health with a
quar billion dollars that that's going
to get your attention and certainly the
co-pilot is the GitHub co-pilot is one
of the very early seemingly highly
reliable uses of AI like we're seeing it
really impacting the coding world and so
you're going to see some competition
flow into this space so yeah just again
things that kind of perk our ears up is
when you hear a quarter billion in
funding and see Eric Schmid's name tied
to something and and the founders from
Google and Microsoft definitely a up
worth paying attention
to all right you know it wouldn't be AI
news without Elon Musk being in the news
again Elon musk's AI company xai which
makes grock the AI assistant that he has
is reportedly close to raising $6
billion from investors that include
Sequoia Capital this raise would value
the company at $18 billion and according
to the information it's expected to
close in in the next 2 weeks now
according to their reporting the company
is currently training the second
generation of grock on 20,000 Nvidia
h100 chips and musk has also indicated
that the company needs 100,000 gpus to
train grock 3.0 so that's likely where
at least some of this money is going but
really kind of big question I have here
Paul is like you've been I mean we both
have been pretty underwhelmed but with
grock like in our initial test T is this
kind of valuation Justified for this
company or this tool I mean Elon sells
Visions like no gr is useless right now
still again I if someone has a use for
grock like please reach out to me and
tell me how you're using the thing I I I
just don't understand like what what
it's supposed to be doing um but he he
sells Visions like we're going to go to
Mars we're going to Electrify the world
with cars and um you know that that's
his thing and so I'm sure he's just in
some Grand Vision for AGI and and its
embodiment into robots and how it's
going to accelerate you know getting to
Mars and um you know saving the planet
so and he can get money from people
whether it's seoa or um you know other
government uh funds um is certainly a
place he tends to tap he which creates
some of the friction between him and the
US government is elon's very friendly
with other governments that the US
doesn't necess necessarily want him to
be friendly with and because it's a
source of money for him so yeah I don't
know I keep keep watching grock maybe
it'll uh do something at some point I
don't know but yeah I I wouldn't be
shocked if he raised this I wouldn't be
shocked if it was more money than this
like he can raise whatever he wants
probably
yeah all right next up we have gotten
news that Apple has started backup
discussions with open AI about using its
AI to power new iPhone features coming
later this year this comes from some
reporting by Bloomberg these discussions
revolve around the terms of a possible
agreement between the two companies that
would integrate open aai features into
iOS 18 which is the next iPhone
operating system now earlier this year
apple and open aai apparently had been
talking but it looks like those talks
had stalled until now apple is also in
discussions with Google to potentially
license their Gemini models free use in
their products so Paul these are still
discussions and rumors not any actual
deals yet but you're a longtime Apple
Watcher like why is Apple engaged in
trying to use AI from other companies
rather than building their own I think
they're doing all the above I I mean who
hasn't Apple had talks with at this
point or at least reported to have talks
with so I don't know I mean but Apple's
done deals with everybody for the iPhone
at different times so nothing would
shock me if they do a deal with open a
or Microsoft or Google like I mean
they're Frenemies they're sometimes they
do deals together and other times
they're competing against each other so
I'm not surprised by any of it I have no
idea what they're going to do it seems
like it's going to be a mix of their own
models so again if you read the recent
research reports coming out of apple
which they're not historically like one
to put out a bunch of research yeah so
they've been talking a lot about their
their investements internally with AI so
I I think there's just going to be a mix
and it may be that they're not fully
baked yet with their internal models and
so they're going to do deals with other
companies until they feel that their
models are you know ready for prime time
I don't know but they're going to do
something like they're they're going to
make some major announcements in June
and I would expect that by this fall the
way your phone works is probably going
to start to evolve like we're going to
experience AI on device
um as soon as this fall so one way or
the other definitely something to keep
keep an eye
on all right our last story this week is
about HubSpot because HubSpot just
unveiled its most recent Spotlight so
this is a product showcase the company
says it's rolling out twice a year to
kind of highlight new parts of the its
various hubs and other products and AI
played a starring role in this one
because HubSpot says it has started to
embed AI across each one of its hub
products across Marketing sales and
service and this Spotlight showcases
some of the latest AI features and these
include things like a feature called
clip Creator which generates videos from
text prompts an AI powered automatic
reply system in their service Hub the
ability to turn written content into
audio with AI powered blog post naration
the ability to create reports
automatically using generative Ai and
text prompts there's AI powered brand
voice which generates content that
sounds like your company they have now
predictive AI to forecast sales
performance and much much more now Paul
we've obviously got a very long history
with
HubSpot you know this isn't the first
time they've released AI features but
how do you see these updates kind of
fitting into hubspot's overall AI
trajectory they're they're pushing out a
lot of updates
um they they're really logical use cases
it's uh good to see them keep making
Innovation I I saw some chatter just in
like the partner Channel I'm still like
observe I'm not involved in it anymore
but just that like people are struggling
to keep up with the update I think there
was like over a hundred things in in
this Spotlight and the way they released
it is like this this page that's just
like this infinite scroll page of
updates I don't know if there's like a
way to download this like I was having
trouble honestly like kind of even
figuring out what was going on and what
what all the updates were and what we
have and don't have as a company um
because again we as you said we use it
and I'd love to know like okay which are
the things that actually matter to us
I'm not going through a hundred things
and figure out what to actually use here
maybe they could build an AI bot that
advises you on what to use um that's
connected to your Hub that says hey
you're because I know I mean God going
back to like 2008 they used to track
like individual usage of individual apps
it's how they knew how you know their
happiness factor for a customer is based
on your app usage within the platform
and that was reported to Partners like
they know what we're using what we're
not like maybe I could talk to their
little AI chat bot and it could tell me
like here's ways you could use AI like
that would be cool um because this is a
lot to process but good to see them
continuing to push out AI updates for
sure all right Paul that's a wrap for
this week we really appreciate as always
you breaking down what's going on in AI
this week um just some final notes here
I would just highly encourage anyone
who's getting value out of the podcast
please leave us a review on your
podcasting platform of choice it helps
us get the podcast into the ears of more
listeners and I would also just
reiterate if you do have a few minutes
and you haven't taken our state of
marketing AI survey yet please go to
state ofmarketing
a.com we are keeping the survey open for
the next uh about 6 weeks here and we'd
love to hear from you about how you're
using artificial intelligence it should
only take a couple of minutes for you to
fill out and it helps us move the
industry forward by publishing really
robust research on AI adoption and then
last but not least please go check out
our newsletter this week in AI at
marketing AI institute.com
newsletter it covers more in depth all
of the news we discussed today and also
all the topics we don't have time to get
to so it's a single comprehensive brief
to get you caught up on AI in just
minutes that comes out every week so if
you haven't signed up for that I highly
highly encourage it Paul until next week
thank you again for breaking it all down
for us I have a feeling this week's
going to like make up for last week I
think there's G to be a lot happening
this week so we will be back with you
next week reporting all the news uh that
matters to you um yeah have a great week
everyone we'll talk to you again soon
thanks for listening to the AI show
visit marketing AI institute.com to
continue your AI Learning Journey and
join more than 60,000 professionals and
Business Leaders who have subscribed to
the Weekly Newsletter downloaded the AI
blueprints attended virtual and
in-person events taken our online AI
courses and engaged in the slack
Community until next time stay curious
and explore AI
関連する他のビデオを見る
![](https://i.ytimg.com/vi/Y9owkFdn40s/hq720.jpg)
Reviewing the AI Battlefront | The Brainstorm EP 38
![](https://i.ytimg.com/vi/O77UyYK51s4/hq720.jpg)
Sam Altman CEO of OpenAI | Podcast | In Good Company | Norges Bank Investment Management
![](https://i.ytimg.com/vi/6H8NPVGC6Ak/hq720.jpg)
Microsoft MASSIVE Announcements: GPT-5, Copilot+ PC, Phi-3, Devin Partnership
![](https://i.ytimg.com/vi/07B5Q8qLBdo/hq720.jpg)
ChatGPT resta indietro, deepfake irriconoscibili, algoritmi emotivi
![](https://i.ytimg.com/vi/fJa0AebITaA/hq720.jpg)
Questa AI fa il mestiere di 700 persone, robotica che cambia la vita, l'AI arriva nelle tue orecchie
![](https://i.ytimg.com/vi/rgF6nhRAZxI/hq720.jpg)
Microsoft BOMBSHELL Announcements: Sam Altman on GPT-5, Devin Joins Microsoft and Phi-3 (SUPERCUT)
5.0 / 5 (0 votes)