The AI Daily Brief (Formerly The AI Breakdown): Artificial Intelligence News and Analysis
Google's AI Co Scientist and the True Power of Multi-Agent Systems
Sat, 22 Feb 2025
Google’s AI Co-Scientist is changing how research gets done, using a system of multiple agents working together to generate and refine scientific ideas. This approach has already led to drug repurposing, treatment discovery, and antimicrobial resistance research breakthroughs. But beyond science, this model hints at a more significant shift in multi-agent AI systems tackling real problems. Are we about to see a wave of AI teams replacing single models?Brought to you by:KPMG – Go to www.kpmg.us/ai to learn more about how KPMG can help you drive value with our AI solutions.Vanta - Simplify compliance - https://vanta.com/nlwThe Agent Readiness Audit from Superintelligent - Go to https://besuper.ai/ to request your company's agent readiness score.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/1680633614Subscribe to the newsletter: https://aidailybrief.beehiiv.com/Join our Discord: https://bit.ly/aibreakdown
Chapter 1: What are the latest headlines in AI?
Today on the AI Daily Brief, Google's AI co-scientist shows the future not only of scientific research, but of multi-agent systems. Before that in the headlines, is meta-AI going enterprise? 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.
We kick off today with some interesting intrigue around Meta and their AI strategy. This is something I've been watching closely. I think a lot of people have wondered, is Meta going to try to compete in the enterprise or corporate domain? Or are they just going to try to own consumer AI or at least the foundations and underpinnings of consumer AI? Certainly, Meta is at core a consumer company.
Facebook, WhatsApp, Instagram, these are all consumer products that touch a huge portion of the world's population. And even their interactions with businesses are mostly in the form of selling them ad space to sell to those consumers. Lama, though, is really interesting because Lama as a platform and as the vanguard US open source AI leader has a ton of potential in that enterprise sphere.
And so I've been wondering if they were going to make a play for that space. This got a little bit more interesting last November when Meta poached Clara Shi from Salesforce. She had been the CEO of Salesforce AI and joined Meta to explicitly start a new group that was building AI tools for business.
Subsequent to joining Meta, it sounds like she went and recruited a bunch of people from throughout the company who had worked on some of the key products. The speculation is now about what they're actually going to do.
One thing that the information point out is that last year they had posted a role called Director of Public Senator Engagement that was responsible for, quote, building and leading a high-performing team from the ground up to drive adoption of safe and transformative solutions for AI across federal, state, and local government agencies.
And just before it had posted that role, interestingly, Meta had also started to allow its AI models to be used by the U.S. military. Right now, it's all still very mum, but you're starting to get the type of leaks and intrigues that suggest that maybe they're going to make bigger play in the enterprise.
Certainly from the standpoint of super intelligent, that's something we're watching closely as it would absolutely be a player and change the calculus for big enterprise companies thinking about their AI and agentic strategies.
Speaking of big companies, apparently money talks and BS walks because despite years of lambasting Microsoft and all the other big companies, Salesforce is now in talks with Microsoft, Oracle, the company they were basically designed to disrupt, and Google about cloud deals to handle their AI.
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Chapter 2: Is Meta making a move into enterprise AI?
There are many reasons I'm excited about AI. We touched on this a little bit earlier. The most, personally, the single thing I'm most excited about is what this is going to do for scientific discovery. I believe that if we can accelerate scientific discovery, we can do 10 years of science in one year, and then someday 100 years of science in one year.
What that will do to quality of life, like solving our most pressing problems, addressing the climate, making life just better in all sorts of ways, curing disease, that will be an incredible gift. And I think AI is finally going to enable that.
So that's a really big, bold pronouncement. And it's something that Altman and others have said a lot. The question for many has, of course, been, okay, but how? Because one thing that's clear is that the current crop of LLMs isn't off making scientific discoveries on their own. So then, is it about underlying models and them just needing to be smarter? Or is it about something else?
Well, what it looks like after reviewing this new Google announcement is that it's not just about the model. It's about how specific agents using models come together to do work. So earlier this week, Google posted on their company blog, Today, Google is launching an AI co-scientist, a new AI system built on Gemini 2.0 designed to aid scientists in creating novel hypotheses and research plans.
Researchers can specify a research goal, for example, to better understand the spread of a disease-causing microbe, and the AI co-scientist will propose testable hypotheses along with a summary of relevant published literature and a possible experimental approach. AI co-scientist is a collaborative tool to help experts gather research and refine their work.
It's not meant to automate the scientific process. Okay, so that's the overview, but where it gets really interesting is in their longer blog post where they actually explain this all. First of all, it's clear right from the beginning that part of the opportunity comes from new long-term planning and reasoning capabilities of models. The goal is really ambitious.
They write beyond standard literature review, summarization, and quote-unquote deep research tools, the AI co-scientist is intended to uncover new original knowledge and to formulate demonstrably novel research hypotheses and proposals. So how does it do this? Google writes, to do this, it uses a coalition of specialized agents.
Generation, Reflection, Ranking, Evolution, Proximity, and Meta Review. In their most simple pictorial diagram, they show three elements. The first ingredient for this is test-time compute, this new approach that is underpinning reasoning models.
Then they show this group or team of individual agents who all have a different function, organized under a supervisor agent, all of which are, of course, organized under a scientist. Then lastly, they have a research ideas tournament that shows how new ideas are proposed, evaluated, and refined. So let's get more into these specific agents. First comes, of course, the scientist.
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