The AI Daily Brief: Artificial Intelligence News and Analysis - More Than 1/4 of Google's Code Now Generated by AI
Episode Date: October 31, 2024More than a quarter of Google’s new code is now generated by AI, signaling a major shift in software development. As GitHub Copilot adds models from Anthropic and Google, developers are gaining more... options than ever. This trend suggests that AI is set to redefine coding, making software creation faster and more accessible across the tech industry. Concerned about being spied on? Tired of censored responses? AI Daily Brief listeners receive a 20% discount on Venice Pro. Visit https://venice.ai/nlw and enter the discount code NLWDAILYBRIEF. The AI Daily Brief helps you understand the most important news and discussions in AI. Subscribe to the podcast version of The AI Daily Brief wherever you listen: https://pod.link/1680633614 Subscribe to the newsletter: https://aidailybrief.beehiiv.com/ Join our Discord: https://bit.ly/aibreakdown
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Today on the AI Daily Brief, Google reveals that more than a quarter of their new code is now generated by artificial intelligence.
Before then, in the headlines, Elon's XAI is apparently raising new funding at a $40 billion valuation.
The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI.
To join the conversation, follow the Discord link in our show notes.
Welcome back to the AI Daily Brief Headlines edition, all the daily AI news you need in around five minutes.
We kick off today with the latest funding rumor,
In the wake of OpenAI's massive $157 billion valuation round,
Elon Musk's XAI is looking to raise billions as well
at a valuation that if not the stratospheric $157 billion is still very high.
According to Wall Street Journal reporting,
the company is in talks to raise at a $40 billion valuation.
The news comes just five months after XAI's previous round,
which raised $6 billion on a $24 billion valuation.
Since then, the company has completed construction
of the colossus supercomputer at record speed
and rolled out multiple new features, meaning that to some investors, the jump in valuation is likely
justified. The journal emphasized that the deal is still in its early stages, so is subject to change
or abandonment. Musk's plans for the money are pretty clear. On a video called Tuesday into a
conference in Saudi Arabia, Musk said, if you're training a frontier model, you need a massive
amount of compute. On Monday, he confirmed plants to double the size of the Colossus training cluster
by adding an additional 100,000 GPUs. Nikolae Yakuvenko writes,
Elon wants a true open AI competitor. And say what you,
you will, but Elon's companies rarely fail to raise the money they ask for. The Elon Fax
account, which I will let you decide what it's likely bias is, pointed out that Nvidia CEO Jensen Huang
recently said, building a massive supercomputer factory in the short time that was done that is superhuman.
There's only one person in the world who could do that. What Elon and the XAI team did is singular,
never been done before. Everardai's Jayazang writes underrated XAI and Google, accurately rated
OpenAI, Anthropic, and Meta. And I actually think that the bigger point here is not so much the
underrated or accurately related designation, but the fact that when it comes to frontier models,
if you are actually trying to compete in that space, if you are an investor who has a thesis,
that the value proposition of AGI is going to be so large that effectively any price is worth it
to invest in, these plus mistral are pretty much the only way you can make that bet,
which means that the price is fairly inelastic. Now, we had previously gotten reports that Anthropics,
had also floated $40 billion in its own funding talks,
and my guess is that if Elon is coming anywhere near close to that,
Anthropics is going to use that fact to try to go for something even higher than $40 billion,
making the argument that they are proportionally farther ahead than Elon is.
Who knows, though, we will have to wait and see.
Meanwhile, some interesting hardware news,
OpenAI will reportedly have their own custom-designed AI chip ready to use by 2026.
According to Reuters, the company has explored all options to diversify their chip supply and reduce costs,
considering building everything in-house and raising capital to build a network of chip foundries,
but now it appears that they've abandoned those plans due to cost and time constraints.
Instead, according to Reuter's sources, they are opting to focus on in-house chip designs.
The plan will now involve partnering with Broadcom or TSM for manufacturing,
while adding AMD alongside Nvidia as a supplier.
The first AMD installation will come through Microsoft Azure,
who are using the company's MI300X chips.
Those chips are not as performing as Nvidia's H-100s in training,
but have outperformed in inference benchmarks.
Sources said that OpenAI had already been working with Broadcom for months to produce their first inference chip.
Currently, GPU supply has been bottlenecked by strong demand for training chips, but there's a chance that inference will become the scarce resource as more AI applications are deployed.
OpenAI have reportedly assembled a 20-person chip design team led by top former Google engineers, Thomas Norrie and Richard Ho.
Sources also say that the firm has secured manufacturing capacity from TSM in 2026.
OpenAI, CFO, Sarah Fryer referenced the growing pains as the company learns to create its own data centers in chip.
during an interview earlier in the week, stating,
it's definitely a stretch from a capital perspective, but also my own learning.
Frankly, we are all learning in this space.
Infrastructure is destiny.
Salesforce, which is making a huge bet on agents,
has finally released them broadly via their new agent development platform agent force to the public.
The product is essentially a low or no-code way of building and deploying
agenic chatbots for employees and customers.
Salesforce outlined a key use case in a post highlighting the upgraded functionality,
writing, your customer at midnight asks, I need to change my entire order.
Traditional bots say, I've created a ticket.
Please wait 24 to 48 hours.
Agent Force service agent, order updated, shipping rerouted, confirmation sent anything else.
In a press release, the company said, agent force doesn't depend on human engagement to get work done.
These agents can be triggered by changes in data, business rules, or pre-built automations.
Now, Salesforce CEO Mark Benioff has recently become the leading voice saying that the assistant
era was all BS and that everything is about agent.
agents, which is clearly marketing, given where they sit, and a way to poke at Microsoft.
But still, I think it's pretty exciting to start to see these agents actually rolling out
in a real way.
We'll soon be able to see a lot more around how well they work in practice.
That, however, is going to do it for today's AI Daily Brief Headlines edition.
Next up, the main episode.
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this AI enablement network. And now back to the show. Welcome back to the AI Daily Brief. Today we are
talking about what is an absolutely insane statistic. Yesterday, Google reported quarterly earnings,
and on the analyst call, Google CEO Sundarpa Chai was asked effectively about the effectiveness
of AI, how much it was real, how much it was hype. And one part of his response was that he said
that more than a quarter of all new code at Google is being generated by AI than reviewed and
accepted by engineers. Now, there was a lot of other stuff on this call as well. AI, for example,
is helping drive revenue at Google. Google, Google's
cloud business, which includes its AI infrastructure products, was up 35% year over year to 11.4 billion.
But this stat around how much Google is dog-fooding AI was really the headliner.
But Chai went on to say that AI for coding was, quote, boosting productivity and efficiency,
and that this helps our engineers do more and move faster.
I'm energized by our progress in the opportunities ahead, and we continue to be laser-focused
on building great products.
Of course, as business insider points out, as impressive as this number is, there may be some
who get a little bit nervous hearing it. The new data from Pichai will surely have some
employees wondering whether they're coding themselves out of a job. Company leaders have previously
promised that AI isn't taking Googler's jobs yet, but the over 25% figure is striking and
underscores the benefits of improving this technology. A lot of the discussion on X slash Twitter
was around the implication for developers. Audit Sheath writes, if you're a programmer
hesitant about using AI and trust me some are, it's starting to look like resisting it might mean
getting left behind.
Rohan Paul writes,
connecting the dots,
Google laid off its entire Python team
in April 2024 as part of a cost-cutting effort.
Today, it's revealed on the earnings call
that more than 25% of all new code at Google
is generated by AI.
Software engineering will be disrupted
in more ways by AI than we can see right now.
He also went on to make a prediction,
I think that the next 10 years is the last period
that any human will ever write any code.
Others tried to connect it to their own industries.
Lawyer Danielina Jr. said,
if more than 25% of new code at Google is generated by AI and then reviewed by engineers,
I find it quite plausible that the same is possible in law if we do the work to build capable
systems. There are differences in the ecosystems and we need to close those gaps.
Derej Nambiar writes,
First, AWS and now Google are automating large amounts of their code generation with the use of
Gen AI. Software engineers that don't leverage AI extensively have one, maybe two years of shelf
life. Investor Stevensonovsky made the point that ultimately, users don't really care around
how products were built. They just care that they work.
He wrote, in the early days of the micro-computer software was written in assembly.
Then C got introduced to the micro and all the industry was asking of each vendor was
will you move to C and when.
That was because C was viewed as faster and easier to use and created less bugs.
It was a modern, higher-level language.
Soon the biggest vendors all announced that their next versions would be in C.
This happened again in 1990 or so with the rise of object-oriented.
Soon vendors were claiming that their products were O-O and thus imbued with all the magic
beans that came from that.
They would be easier to maintain, have fewer bugs easier to add new features.
Nope, that wasn't true either. Then everyone began to doubt those techniques. No one cares what tools
companies used to write code, not consumers, or even enterprise. They care about features, cost,
quality, security, reliability, privacy, and performance to name a few. If new tools helped, then great.
If new tools don't help, then that's not good. It's even worse if the companies are out there
touting new tools and not delivering. Still, Ravu Tanuku summed up the point of Sundar's comments saying,
this says to Wall Street, we are getting leverage on AI spending. It portends what less
sophisticated tech companies can accomplish over time. It implies ROI is happening and giving
a reason why they should keep spending on it. I will take a minute here to get up on my bully
pulpit once again and to talk about the two phases of generative AI adoption. Once again,
there is inevitably going to be a phase where companies treat AI as exclusively an efficiency
technology, a way to get the same output with less input, a cost-saving technology that will in
many cases lead to job cuts, lower overall costs, and the markets are likely to reward it, at least in the
short term. However, the companies that win in the generative AI era, I'm quite convinced,
will be those who view generative AI as an opportunity creation technology, a way, in other words,
to do more with the same, or much, much more with just a little more. When it comes to developers,
I am firmly on the other side of, in 10 years we won't have any humans writing any code,
or at least I'm on the other side when it comes to humans producing code. I think that we are
going to have hundreds and hundreds or thousands of times the code that we have now. I think more
people are going to be producing code with the help of both assistants and agents, and I think that
means more things are going to be built. But in the in-between, it's going to get weird, and even as
someone who watches this every day, hearing that Google is already generating a quarter of its code
with AI is fairly surprising. Two other interesting Google nuggets from the earnings call, one small and
one bigger. The small one is that Google says that they won't ship agentic features until next year at
the earliest. The feature known as Project Astra was previewed at the I.O. Developer Conference in May.
It encompasses a range of functionality, including a smartphone app that can recognize the world through the camera,
to AI assistance that can complete tasks autonomously.
On that same earnings call, CEO Sondarva Chai said,
Google is building out experiences where AI can see and reason about the world around you.
Project Astra is a glimpse of that future.
We're working to ship experiences like this as early as 2025.
You might remember that the information had previously reported that Google was planning to ship
their first agents known as Jarvis as early as December,
but now that timeline seems a little bit unclear.
Maybe the bigger deal is that Microsoft's GitHub co-pilot will now support models from Anthropic
and Google alongside OpenAI. Users will be given the choice of model between Claude 3.5 Sonnet,
Gemini 1.1.5 Pro, as well as Gptv0, O1, O1Mini. GitHub's CEO Thomas Domke said,
there is no one model to rule every scenario, and developers expect the agency to build
with the models that work best for them. It is clear the next phase of AI code generation
will not only be defined by multimodal functionality, but by multimodal choice.
Microsoft, of course, introduced GitHub co-pilot in 2021, making it one of the first products to demonstrate
the power of AI assistance. It had previously relied solely on models provided by OpenAI.
The arrival of OpenAI's 01 models led GitHub to explore the idea of a drop-down menu to provide
easy access to model options. Domki said at that point it felt like the right time to expand to other
companies as well. He added, we're planning on extending that list in the future but have no
partnerships to announce at this point. GitHub has also introduced a new automated code review feature,
and next up on the feature list is a powerful app designing tool called Spark.
The feature will allow developers to create app prototypes based on text prompts and then refine
the designs from there.
Domke said, for too long there has been an unscailable barrier of entry separating the vast
majority of the world's population from building software.
With Spark, we will enable over 1 billion personal computer and mobile phone users to build
and share their own micro apps directly on GitHub.
Now, of course, the subtext and context of this announcement is both one, what appears
to be a potentially fraying relationship between Microsoft.
Microsoft and OpenAI. And two, of course, the battle between Open AI and Anthropics models when it
comes to code assistance. Developer Nick Dobos writes, GitHub co-pilot adopting Klaude and Gemini is the
final nail in the coffin for base model companies. AI infrastructure is a difficult business to
compete in even if they are producing amazing technology. Application layer wins, rappers all day,
every day. Super fascinating. I don't really know how much to read into this when it comes to that
open AI relationship piece. It certainly does put evidence in the column of those who think that
base level models are going to be commoditized.
But no matter what, it's a pretty big shift and one that'll be worth watching over time.
For now that, that is going to do it for today's AI Daily Brief.
Until next time, peace.
