Welcome to the Daily AI News Podcast.
We're diving deep into all those articles
you've been reading about AI,
especially how it's changing things for developers.
It's a really exciting time to be building software.
Totally.
We've got a ton to cover from GitHub Universe 2024,
plus VentureBeat, even some security stuff,
and some quick hits from earnings calls.
We'll try to make sense of it all,
give you the big picture of where AI is heading
and what it means for developers.
Sounds good.
So first up, GitHub Universe 2024.
Microsoft was all about AI native development,
which sounds kind of futuristic.
It really is about changing how we think
about building software,
not just adding AI features,
but making AI central to the whole process.
So not just like an add-on.
Right, more like baking it into the DNA
of software development from the start.
I like that analogy.
And a good example of this is GitHub Copilot,
which is getting a lot more powerful.
Yeah, they've made some big changes.
Like you can now choose from different AI models,
not just one size fits all.
There's Anthropics, Clawd 3.5, Sonnet,
Google's Gemini 1.5 Pro,
and even OpenAI's 01 Preview and 01 Mini.
So developers can pick the AI that works best for them
and how they code.
And it's not just about writing code anymore.
Copilot can do code reviews, security checks,
even works right in your terminal.
It's like having a super-powered AI assistant
who's always there to help.
I definitely need one of those.
Then there's this experimental thing called GitHub Spark,
which lets you build these little apps
just by using natural language.
It's all about making coding accessible to anyone,
even if you don't know a programming language.
That's really cool.
Okay, so continuing on this whole Microsoft thing,
the VentureBeat article we have
dives into their strategy to,
well, kind of dominate AI app development.
They're going all in for sure.
Yeah.
A big part of that is this GitHub Copilot for Azure,
which is like an AI assistant specifically for Azure.
So it can help developers manage their cloud resources,
deploy apps, even troubleshoot problems,
all without leaving their coding environment.
That sounds super handy.
It definitely streamlines the workflow,
lets developers focus on the code.
And then they've got these AI app templates
that you can use to get started quickly.
You can have an AI app up and running in minutes,
supporting a bunch of different frameworks.
That's pretty impressive.
It does seem like Microsoft is trying to create
this whole ecosystem where everything just works together.
They own GitHub and Azure,
so they're in a good position to do that.
And it'll be interesting to see how this plays out
against like AWS and Google.
It's definitely heating up the competition
in the cloud space.
Okay, let's shift gears a bit and talk about security.
This research paper we have is a little bit scary.
It found a ton of vulnerabilities
in open source AI and ML models.
Yeah, open source doesn't always mean secure.
Like we're talking about tools like ChwantachatGPT,
Lunary and local AI.
And some of these flaws are pretty serious.
Things like remote code execution, data theft,
unauthorized access,
definitely stuff you don't wanna mess with.
And the techniques these attackers are using
are getting more and more sophisticated.
Like using emojis and hexadecimal code
to bypass ChwantachatGPT safeguards.
It's a cat and mouse game.
As security measures get stronger,
attackers find new ways to exploit weaknesses.
So developers need to be really careful
about the open source AI models they use
and make sure security is the top priority.
Absolutely.
Don't assume that just because it's open source, it's secure.
Do your due diligence, check for known vulnerabilities
and implement appropriate security measures.
All right, let's move on to something completely different.
Open AI is now making their own chips.
They're partnering with Broadcom and TSMC
to build AI chips, specifically for inference,
which is how AI models make predictions.
This is a huge move.
Open AI is one of the biggest buyers of NVIDIA GPUs,
but it seems like they want more control
over their hardware and maybe save some money too.
It makes sense.
Those GPUs are super expensive
and training these large AI models can cost a fortune.
And they're not just dabbling in chip design.
They've even hired some of the top engineers
from Google's TPU team.
So they're serious about building
high performance AI hardware.
They even had this ambitious plan
to build their own network of chip factories.
But that got scaled back
because of the cost and time involved.
It's a massive undertaking,
but it shows how committed they are
to this chip strategy.
Speaking of competition, let's talk about Google.
During their Reason Earnings call,
their CEO hinted at the next generation
of their Gemini model,
which is supposed to be even more powerful,
and maybe even have some agent-like capabilities
similar to Anthropics' Claude.
Sounds like it's gonna be a game changer.
And they're already using AI in a ton of different ways.
Did you know that over 25% of new code at Google
is being generated by AI?
That's a lot of code.
It shows how deeply integrated AI is becoming
in their internal processes.
Plus, it's helping them make money
in search, cloud, and YouTube.
Their earnings call showed really strong growth,
driven apart by AI.
Clearly, their AI investments are paying off.
Okay, last but not least,
we've got this emphasis report
that looked at how businesses are adopting AI.
It found that companies are really excited about AI,
expecting a 15% productivity boost on average.
That's a significant improvement.
AI has the potential to revolutionize
how businesses operate.
But here's the problem.
Only 2% of organizations are actually fully AI ready.
That's a huge gap between the aspiration
and the reality of AI adoption.
They found that the biggest hurdles
are lack of technical capabilities
and problems with data accuracy and access.
So it's not just about the technology itself.
It's about having the right foundation in place
to support AI implementation.
Companies need to invest in developing their AI skills,
creating clear data strategies,
and building a culture that embraces AI.
Otherwise, they risk falling behind
in this rapidly evolving AI landscape.
It's not just a technology project.
It's a strategic imperative for businesses
that want to stay competitive in the AI era.
Couldn't have said it better myself.
Yeah, it's amazing to see how fast things are moving,
but let's go back to GitHub Universe for a sec.
There were so many co-pilot updates, it's hard to keep up.
Yeah, I know, right?
Like, the multi-file editing in VS Code blew my mind.
You can tell co-pilot to make changes
across multiple files at the same time, using plain English.
So instead of manually going through each file,
you can just say, like, update all these functions
to use the new API and co-pilot takes care of it.
Yeah, that's exactly it.
It would be a huge time saver,
especially for those giant code bases.
For sure.
It's all about making developers more productive, right?
Totally.
And they've even got co-pilot doing code reviews now.
I know, that's pretty cool.
As soon as you create a pull request,
co-pilot can jump in and give you feedback on your code,
so you don't have to wait for another person to look at it.
Especially useful for smaller teams or solo developers
where you might not have dedicated code reviewers.
Exactly.
And beyond the fancy new features,
they've also improved co-pilot's core functionality,
like code completion and support for languages
like C++ and.NET.
So it's getting smarter all the time.
And more widely available too.
It now works in more tools, like Xcode and Windows Terminal.
They're really making it part of the developers toolbox,
no matter what you're using.
Oh, there's also this co-pilot upgrade assistant for Java
that's in preview.
Have you had a chance to try that out?
Not yet, but it sounds pretty amazing.
So you know how upgrading Java runtimes or dependencies,
like Spring Boot or Junit, can be a real pain?
Oh yeah, definitely.
Especially when you have a bunch of dependencies
and libraries to manage.
It can take forever.
And you're always worried about breaking something.
So many things can go wrong.
Well, this upgrade assistant is supposed to make
that whole process way easier.
Codepilot analyzes your project,
figures out the best upgrade path,
and even helps you transform your code
and fix any issues that pop up.
It's like having an AI expert guiding you
through the upgrade process.
Right, so no more manual dependency, hell.
Fingers crossed.
Speaking of security, we talked about those vulnerabilities
in open source AI models,
but we should also think about the security
of GitHub itself, right?
Oh yeah, for sure.
With millions of developers using GitHub,
keeping that code secure is super important.
It's the foundation of so much software development.
They've been adding more security features,
which is good to see.
What kind of stuff are they doing?
Well, for one, they've expanded
Copilot Auto Fix to open source projects.
So if a vulnerability is found,
Copilot can automatically suggest a fix.
That's pretty cool.
It could really speed up the process
of patching security holes.
Exactly.
And they're also doing these security campaigns
to find and fix vulnerabilities at a larger scale.
So it's not just about individual projects,
but about improving the security of the whole ecosystem.
Right, and it's all powered by AI, of course.
Copilot can help you triage
and fix thousands of security alerts automatically.
It's like having an army of AI security experts
working for you.
I like that.
And beyond just fixing bugs,
they've also added new controls
for governance and compliance.
So admins have more control over things
like user permissions and repository policies.
Those features are super important for big companies
that need to meet strict security
and compliance requirements.
And under the hood,
they've made some performance improvements
to GitHub actions, like faster ARM64 powered runners.
So your workflows and CACD pipelines
will run even smoother.
Always a good thing.
They also announced this new GitHub models platform,
which is basically a place where you can try out
and compare AI models from different providers,
like OpenAI, Coher, Microsoft, and Mistral.
Kind of like a marketplace for AI models.
Exactly.
You can even use the GitHub models CLI extension
to access and run these models from your terminal.
They're really going all in on AI,
integrating it into every part of the developer experience.
It really does feel that way.
Okay, before we move on,
remember that Infosys report we talked about earlier
about businesses struggling to become AI ready?
Yeah, we're only 2% are actually fully prepared for AI.
Right, well, they broke down AI readiness
into these five key areas.
Talent, strategy, governance, data, and technology.
Those are the building blocks of successful AI adoption.
And they're all interconnected.
You can't just focus on one and ignore the others.
It's like trying to bake a cake without all the ingredients.
So for companies that are serious about using AI,
what are some concrete steps they can take
to improve their readiness?
The first thing is to honestly assess
where they stand in those five areas.
Figure out their strengths and weaknesses,
where the gaps are,
then they can start building a roadmap for improvements.
So kind of like taking inventory.
Exactly, figure out what you have,
what you need, and how you're gonna get there.
And it's not a one-time thing, right?
It's an ongoing process.
Absolutely.
The AI landscape is constantly changing,
so companies need to be constantly learning,
adapting, and upgrading their capabilities.
Okay, back to GitHub Universe one last time.
They announced something called GitHub Copilot Extensions,
which is a platform for building
and sharing your own custom Copilot extensions.
I saw that.
It's like they're opening up Copilot to the community,
letting developers create their own personalized extensions.
You could build an extension to streamline your own workflow,
or even integrate a proprietary tool,
and then you can share your creations
on the GitHub marketplace.
It's like an app store for Copilot,
which is pretty cool.
It's a really smart move by Microsoft.
It encourages innovation and collaboration around Copilot.
It's a win-win.
Developers get more powerful tools,
and Microsoft gets a thriving community
of Copilot enthusiasts.
I think that covers everything from GitHub Universe.
It was a busy event.
Lots of exciting announcements.
Okay, let's switch gears and talk about Google's AI ambitions.
What have they been up to lately?
Yeah, it seems like Google's putting AI
into everything these days.
They're really going all in,
especially with that new Gemini model coming out soon.
Which, by the way, sounds incredible
from what they've hinted at.
It's supposed to be a huge leap forward in AI capabilities.
But even beyond Gemini,
they're integrating AI into all their products.
Yeah, like Search, for example.
Which is still their biggest thing, right?
How are they using AI to make Search better?
They're using AI to understand what you really mean
when you type in a search query,
not just matching keywords.
So it's more about intent, not just words.
Exactly.
It's about giving you the most relevant results,
even if you don't use the exact right words.
That makes sense.
And then they've got those gems,
which are like AI chatbots you can customize.
They're kind of like personalized AI assistants
tailored to specific tasks or areas of expertise.
So instead of a general purpose chatbot,
you could have a gem that's specifically designed
to help you with, say, writing code or planning a trip.
Exactly.
It's about making AI more accessible
and useful for everyone.
And on the business side,
they're investing a lot in AI for Google Cloud.
Oh yeah, they're offering all kinds of AI tools
and services for businesses,
everything from machine learning frameworks
to pre-trained models to even custom AI solutions.
It seems like every cloud provider
is trying to do that now, though, right?
Yeah, but Google has a strong advantage
because of their expertise in AI.
They've been investing in AI research for years,
and they have some of the best AI talent in the world.
Plus they have a ton of data,
which is essential for training AI models.
And it's working.
Their latest earnings call show
that Google Cloud revenue is growing rapidly,
thanks in part to their AI offerings.
Circling back to GitHub Universe for a second,
do you remember how Microsoft kept talking
about making GitHub more enterprise grade?
Yeah, they're definitely targeting bigger companies
with these new features.
Like the data residency
for GitHub Enterprise Cloud in the EU.
Oh yeah, that's a big deal for companies
that need to comply with GDPR
and other data privacy regulations.
Now they can keep their code and data within the EU,
which is a big relief for a lot of companies.
And it shows that GitHub is serious
about meeting the needs of enterprise customers.
They also made some big improvements to GitHub issues,
like adding sub-issues and advanced search.
Which is great for managing
those really complex projects
that big teams often work on.
It's all about making GitHub a more powerful
and scalable platform for enterprise development.
And they also added new controls
for governance and compliance,
giving administrators more control
over security and user permissions.
So they're really tightening up security
and making GitHub more enterprise ready.
It's a smart move considering how many businesses
rely on GitHub for their software development.
And lastly, they made some under the hood improvements
to GitHub actions, making it faster and more efficient.
Always a good thing.
Developers love it when their tools
are fast and reliable.
Okay, so that wraps up GitHub Universe.
It was a packed event for sure.
Lots of interesting stuff to think about.
Especially all the AI announcements.
It really does feel like AI is changing
everything about software development.
So before we finish up,
what's the one key takeaway
you want to leave our listeners with?
Embrace the change.
AI is here to stay,
and it's going to transform how we build software.
Don't be afraid of it.
See it as an opportunity to learn new skills
and become a more powerful developer.
It's not about replacing developers.
It's about giving them better tools and superpowers.
Exactly.
AI can automate tedious tasks,
provide valuable insights,
and help us build more innovative
and sophisticated applications.
Well said.
Thanks for joining us for this deep dive
into the world of AI.
It's been a pleasure.
Always fun to talk about the future of software development.
Thanks for listening to the Daily AI News Podcast,
and we'll catch you next time.