The Ledger
Every statement that passed quotation and attribution checks. Mix any filter with any other: certainty 1/5, debate potential 5/5, or both at once.
why aren't all 42 resolved? a statement only gets an assessment when the public record can support or contradict it. opinions and what-ifs never can, and 0 checkable ones are still open, waiting for their date. predictions held up or didn't; assertions are supported or contradicted. on every card: ▮▮▮▮▮ certainty · ▮▮▮▮▮ debate potential. speakers are clickable
Wood: Claude 3.5 Haiku Outperforms All Other Models on the Planet
“Claude III.V Haiku outperforms all other models on the planet.”
AWS's Wood: Foundation AI models will diversify rather than become commodities
“My guess is that these models will not, you know, kind of commodify. My guess is that they will diversify increasingly over time, and that the idea that there's, these models will become commodities Defined as, you know, you can hot swap them and that their ec…”
Wood: AWS customers saw their proprietary IP output back by ChatGPT
“We've seen actual customers see their own IP come back to them from the model, and that is terrifying to enterprise customers, where the IP is the crown jewels”
Wood argues public web data is fair game for AI model training
“Who's to say what this data can be used for when it's publicly available. You know, you chose to make it publicly available. If you want to put some permissions around it, or you want to take it private, Yeah, that's totally up to you. You still own the data. …”
Matt Wood: Regulated industries are adopting GenAI faster due to existing data governance
“There is a group which is moving slightly faster than the average, which is somewhat Counterintuitive. And that group is actually the regulated industries. And so it's folks like in financial services and insurance and healthcare and life sciences and manufact…”
AWS's Wood: AI agents will be the apps of the generative AI era
“I think agents have a good chance of being the apps for the generative AI world and the generative AI era. And that as we add more of those and we find ways to orchestrate multiple agents together, and there's already customers that are building multi-agent sy…”
Wood: Amazon Q Code Acceptance Rate Is 35% to 50%
“We've seen some customers get, you know, in terms of just the amount of code that is automatically generated that they accept. It's usually between 35 and 50%. It's higher on Q than any other comparable service”
Wood: Smaller specialized models beat frontier models on deep enterprise tasks
“I am absolutely positive that the inverse is also true. That you can find older, smaller, specialized models, ah, that, ah, will, ah, will offer much better, higher quality, lower hallucination results on specific tasks at the depth that most organizations nee…”
AWS's Wood predicts foundation AI models will consolidate to 12-24 major providers
“I think that there's not going to be hundreds of world model providers. I think that there's likely to be maybe a dozen, two dozen, something of that order of magnitude. I think that, you know, Anthropic will be one, Meta will be one, Amazon will be one, there…”
Wood: There will not be a single AI model to rule them all
“We think that there's not going to be a single model to rule them all.”
Wood: Amazon's AI goal is pragmatic utility, not Artificial General Intelligence
“Others are talking about, well, our stated goal is that we want an artificially generally intelligent system. That is not our stated goal. Our stated goal is that we want to just be very pragmatic, meet customers where they're at today, and then provide capabi…”
Wood: AWS Is the Only Cloud for Privately Customizing AI Models
“Today we're the only place where you can take your own data, and we have customers With exabytes of data. You'd be surprised how many customers have exabytes of data on AWS, and they can take that data that they've invested in, and they can use it with these m…”
Wood: AWS's AI business could surpass all other AWS revenue within years
“It seems very low to me, but I wouldn't be at all surprised if just the, ah, AI part of our cloud computing business was larger than the rest of AWS combined in a couple years.”
Wood: Training Net-New AI Models Will Not Be Common
“Yeah, I think training net new models, ah, is not going to be very common. It's, ah, it's very complicated. It is expensive, to your point. You need a lot of compute capacity, a lot of data, a lot of expertise. Some folks that have differentiation in one of th…”
Wood: Gen AI value lies in complex task automation, not chat
“Well, we have the other ones that I mentioned earlier, like the generative pieces, the search pieces, but the collaborative problem solving pieces, the automation pieces, completing complex tasks.
That I think is where the majority of the value is going to be.”
Wood admits Amazon employees already use AI to write six-page memos
“That ship has sailed, I can tell you.”
Wood: Generative AI Functions as a Discovery Exhibiting Emergent Reasoning
“It's much more like a discovery than it is an invention. Ah, we discovered that if you build these very sophisticated mathematical models, that there is emergent behavior within them that resembles reasoning, that resembles intelligence.”
AWS's Wood: Generative AI has not reached its hockey-stick inflection yet
“My guess is that we're, it's probably more likely that we're at the bottom left hand corner. I don't think we've hit the kind of hockey stick inflection point yet. Of what this, ah, what this technology is capable of. It's still very, very, very early.”
AWS's Matt Wood: Web-trained AI models have a six-month shelf life
“Today it looks like models have a shelf life of probably about six months if you're training on kind of open, open web data”
Wood: Chatbots give an appearance of intelligence but fail at complex tasks
“And they give the appearance of intelligence, but they actually are not very good today at completing complex tasks.”
Wood: Vast Majority of AI Compute Cost Is Inference, Not Training
“And whilst A lot of focus is put on training. If you think about it, you may train a model once a month, once a week, let's say, but you're going to be running predictions and inference and chatting with that model 100,010 of thousands of times a day. And so i…”
AWS's Wood: Generative AI Is Too Early to Limit Foundation Model Creation
“Well, on the 81st model, I think you do need an 81st model right now. Like, it would be completely arbitrary to decide right now, at this point in time, that we need to limit the model or that we've got enough. There is so much opportunity. It is so early.”
Wood: Jeff Bezos views generative AI as biggest shift since web browsers
“I think he feels that it is, I wouldn't want to speak on his behalf, of course, but, you know, I think he feels the same. Like, this is the single largest transformational step in how we interact with data and information and each other, you know, since the ve…”
Wood: AWS AI and Machine Learning Business Exceeds Multibillion-Dollar ARR
“Bedrock, which is the service that we make available to customers to build generative AI applications. That's one of our fastest growing services ever. And all up, AI machine learning at AWS is already a multi-billion dollar business. In terms of ARR.”
AWS's Wood: Near-Term AI Progress Will Feel Much More Incremental Than Expected
“I suspect that whilst there will be these step function changes over the long period, I think in the shorter term, in the shorter outlook, it's gonna feel a lot more incremental than we're probably used to.”
AWS's Wood: AI Success Requires 50% Cultural and 50% Technical Investment
“I'd actually say it's more like 50% technical, 50% cultural in terms of the weighting of the, ah, elements of investment that are going to be required to be successful.”
AWS's Wood: 25% to 35% of Enterprise Workforce AI-Ready Today, 100% Long-Term
“I would guess if I had to put a number on it, I would say it's probably 25%, 35% in most large-sized enterprises. But over time, you know, if you look three years out, five years out, 10 years out, whatever it might be, with that long-term horizon, my guess is…”
Wood: Most enterprises will fine-tune existing models rather than build foundation models
“There isn't one model to kind of rule them all. Each different model has, you know, different sweet spots, and it's my expectation that most customers will invest in not building the foundation models, but will invest in fine tuning and improving those individ…”
Wood: AI Startup NinjaTech Has Hundreds of Thousands of Monthly Active Users
“I think Ninja Tech is seeing, you know, remarkable growth. They have hundreds of thousands of monthly active users.”
AWS's Matt Wood confirms Amazon completed its $4 billion Anthropic investment
“Yep, we've completed that investment, yep.”
AWS's Wood: Large language models currently struggle with mapping user intent
“Now, what's funny, the reason it's complimentary is LLMs today are not very good at doing that LLM, you know, intent mapping. They make mistakes. You need to be able to check them, all those sorts of things.”
Wood: Open-source AI models require substantial deployment infrastructure and tooling
“Lama II is a excellent, very capable model, but there is a long way to go from having the model weights which are what comprises the neural network to actually building out an artificial intelligence system. And just having the model weights is super useful, b…”
Wood: Generative AI makes ML far more accessible by eliminating model training
“One of the super interesting things about generative AI is inherently because you're not training the models yourself, you're taking models from Amazon and Meta and a whole host of other stability, AI, and just building on top of them, ah, it makes machine lea…”
Wood: AI agents and output vetting will become as important as models
“So there's a lot of focus on models today, but those models are going to remain important. But over time, there's going to be additional capabilities like agents, like reinforcement learning, like the ability to be able to understand and vet The responses that…”
Wood claims hundreds to thousands of CIOs have banned ChatGPT internally
“THERE ARE HUNDREDS, MAYBE THOUSANDS OF CIOs THAT ARE TELLING THEIR WHOLE ORGANIZATION NOT TO USE CHATGPT.”
Wood predicts generative AI will create multiple Amazon-sized companies
“And I think that there is going to be a wave of similarly Amazon Size companies that evolve out of the generative AI opportunity, generally. And so I think we're going to see multiple Amazon size organizations develop and grow over the next, who knows, 20 year…”
Wood: Using LLMs for search ranking presents a larger commercial opportunity
“The next area, which is Less sexy, but in my opinion, maybe even be a larger opportunity is using this technology to improve search results, improve ranking, relevance, personalization, those sorts of use cases where you don't even know that you're working wit…”
AWS's Wood: Constraints are the single largest force to improve LLMs
“Constraints are probably the single largest force that we have to improve the capabilities of these LLMs.”
Wood: Amazon Titan trained on public web data and licensed datasets
“Titan was trained on publicly available data. And. That's a very squishy phrase. It's very precise. Okay. And data which proprietary data that we had licensed specifically for the purpose of training.”
Stodgy Industries Like Healthcare and Legal Will Yield Earliest AI Returns
“Legal, healthcare, life sciences, clinical trials, drug discovery, all these areas where financial services, insurance, Like, the oldest, stodgiest industries that you can imagine. They've got so much natural language. It's such a large opportunity. I think th…”
Wood: AWS worked with EvolutionaryScale on generative AI drug discovery
“Pfizer or the work we've done with a startup called evolutionary scale to be able to use generative AI to be able to design entirely to entirely new molecules to design entirely new antibodies that are manufacturable that can go on and find new drug targets. L…”