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Welcome back to the AI Daily Brief, headlines edition. All the daily AI news you need in around 5 minutes. We kick off today with a story that seems small but might be an even bigger deal than it feels at first. The TL;DR is that ChatGPT's memory just got a big upgrade. The chatbot will now remember every conversation automatically.
Announcing the feature, OpenAI wrote, "Starting today, Memory in ChatGPT can now reference all of your past chats to provide more personalized responses, drawing on your preferences and interests to make it even more helpful for writing, getting advice, learning, and beyond." Now, up until now, ChatGPT could remember some of your preferences in memory, but the function was pretty limited. Users would need to prompt the chatbot to commit personal information to memory. Kind of useful, but mostly for storing basic facts, like whether you're a vegetarian or have allergies, or what your favorite outdoor activities is, or whatever the relevant context for your common types of requests and prompts. OpenAI said that this new feature would allow ChatGPT to pick up where you left off when you open a new chat window and allow interactions to slowly become tailored to the user. Those who have already opted out of the memory function will have that setting carried over to the new feature, and the two versions of memory can be toggled independently.
AI investor and educator Ali K. Miller believes that this feature will be extremely important moving forward. She wrote, "The best feature in ChatGPT is memory. As models and features get commoditized in AI, it's going to come down to personalization, collaboration, and network effects. Imagine what happens when your memories can be combined." Now, for Ali, this is all about how an otherwise commoditized technology finds a new moat in a very different type of environment, and I think that for investors in ChatGPT, for example, that's absolutely true. For those who are spending any time around agent conversations, memory is something that is getting a slightly bigger and more important place. OpenAI researcher Nome Brown wrote, "Memory isn't just another product feature; it signals a shift from episodic interactions—think a call center—to evolving ones, more like a colleague or friend."
Still, a lot of research to do, but it's a step towards fundamentally changing how we interact with LLMs. Think about it: we are trying to, with agents, build the equivalent of digital employees, and memory and context and understanding is one of those things where there is still a huge chasm between a human coworker and an agentic coworker. An investment in memory is directionally something that's really important for that evolution. Swix from Latent Space in the AI Engineering Summit writes, "Now seems like a particularly opportune time to ask: what are the top memory research papers? Do evolutions for memory differ from long context? Do we want superhuman memory—to never forget—or humanlike memory?"
Now, on that last front, Professor Ethan Malik had an interesting point here as well. He wrote, "I totally get why AI long-term memory is useful, and based on my testing, many people will love it, but I actually don't want my LLMs I use for work to chime in with my personal details or subtly change its answers as a result of my past interactions. Boundaries are good, and I actually do think that it'll be interesting from a user interface perspective if it becomes a challenge to have to basically prompt ChatGPT to not remember certain things. Point being that not all of the things that I asked ChatGPT do I want the context of previous conversations. Now again, that's all solvable with user experience, and ultimately I think the trajectory is extremely important, but it's still fascinating to see how these things will play out."
Next up, Amazon CEO Andy Jassy believes that AI is on the cusp of reinventing every consumer experience and, in his annual letter to shareholders, has said that AI is critical to the company's next phase of growth. He writes, "If your customer experiences aren't planning to leverage these intelligent models—their ability to query giant corpuses of data and quickly find your needle in a haystack, their ability to keep getting smarter with more feedback and data, and their future agenda capabilities—you will not be competitive." The letter also touched on the scale of investment required to take advantage of the AI wave, commenting, "We continue to believe that AI is a once-in-a-lifetime reinvention of everything we know. The demand is unlike anything we've seen before, and our customers, shareholders, and businesses will be well served by our investing aggressively."
Now, during his fourth-quarter earnings call in February, Jassy announced plans to spend 100 billion in capital expenditures this year, with the vast majority going to building out AI capacity at AWS. This is the largest spend of the four big tech giants building AI infrastructure at scale this year, even though Amazon is technically the smallest of the four. Looking at the growth numbers, it's easy to see why Jassy said that Amazon's AI revenue is currently growing at triple-digit year-on-year percentages at a multi-billion dollar run rate. Basically, Jassy's key point was that AI capex should be seen as a leading indicator for long-term profit potential rather than as a red flag for investors. He wrote, "In AWS, the faster demand grows, the more data centers, chips, and hardware we need to procure, and AI chips are much more expensive than CPU chips. We spend this capital upfront, even though these assets are useful for many years." He also noted that the advanced AI capabilities being discussed, quote, "won't all happen in a year or two, but won't take 10 either; it's moving faster than almost anything technology has ever seen."
Finally today, former OpenAI CTO Mira Murati's new company is getting close to closing their seed funding round, and it could be one of the largest in history. Business Insider reports that Thinking Machines Labs is raising upwards of two billion in venture funding. That's twice as much as reported in February when BI said the company would seek 1 billion at a 9 billion valuation. It's not clear how much the valuation has increased during the competitive round, but sources say the new number is at least 10 billion. Although, for those of you doing math out there, if it was a 1 billion on 9 billion post-money, then 2 billion would be inherently a 10 billion post-money. In any case, for a comparison point, fellow OpenAI alum Ilya Sutskever raised 1 billion at a 5 billion valuation late last year for his safe superintelligence company. Murati's company emerged from stealth 2 months ago with very few details. Thinking Machines Labs said they would be working to make, quote, "AI systems more widely understood, customizable, and generally capable," and while the company doesn't have a product or a publicly known roadmap, they do have an extremely capable staff. Their employees include top researchers who previously worked at Meta, DeepMind, and, of course, OpenAI. The company recently added two more ex-OpenAI staff to the mix, hiring former chief research officer Bob McGrew and researcher Alex Radford as advisors. At least one Twitter user, YSquander, assumed that Murati's pitch was pretty simple: OpenAI, but drop the Altman.
That's going to do it for today's AI Daily Brief, headlines edition. Next up, the main…