r/stocks
Anyone else incredibly impressed by Claude Fable? Seems bullish for semis.
Impressed by Claude's reduced hallucinations and tool-use, the author believes AI progress expands the AI TAM, making it bullish for semis.
- Advanced AI models are overcoming hallucination issues by recognizing limitations and autonomously utilizing external tools.
- Reduced hallucinations and increased self-awareness in AI will significantly expand the Total Addressable Market (TAM) for AI.
- Continuous improvements in AI capabilities drive higher demand for underlying computing power, benefiting semiconductor companies.
For instance, I asked it a question about a chess position, and rather than hallucinate and guess, like prior models would have, it went out and downloaded a chess solver called stockfish, installed it onto its operating system (I'm sure that's not the right terminology but you get the point), ran it, and then explained why stockfish did what it did. The fact that it recognized that it would be a tough question to answer, and went out on its own found and utilized a tool was very impressive to me. I know absolutely 0 about coding and had it create a coaching app for myself, the whole process took about 30 minutes. The hallucination issue is one of the biggest obstacles limiting AI TAM, and I'm seeing more and more self awareness out of these models.
No. The biggest amplifiers currently are not the models themselves but the tool calling and agentic harnesses, and the primary proprietary ones are general purpose and terribly inefficient, with no incentive to make them more efficient (cheaper); they are token monsters. Models like Fable are only going to help developers rapidly prototype much better harnesses in rapid time and much more efficient agentic harnesses that adapt to specialize use cases, and pose to drastically undercut the big players who depend on everyone using their inefficient (expensive, high profit) general purpose harness and models, running on overpriced chips. Then people (in China) are just going to use Mythos to distill it into their own models that cost 50X less to run, and then DeepSeek is going to use that to improve their models that use 95% less memory, then everyone is going to forget why they YOLOed into overpriced IPOs that can't afford to race to the bottom.
I'm super bullish on seeing what smart people can do with these models. The business case is running on hopium disconnected from the realities. Agentic programming has absolutely been a game-changer, no doubt, and better models are great an all that (but you dont need that much reasoning in these believe it or not, and you should intentional compact context and limit reasoning models to specific stages in the SDLC).
When you say the business case is hopium, do you mostly mean for the Antropics of the world who will get crushed by the open source models, or do you mean even for applications like radiology, drug discovery, physical AI, materials sciences, math, chemistry, law, document summary, customer service etc?
Yes, the capex doesn't make sense for the big players whose proprietary models and harness that might be a smidge better but cost 30-50X more, and generalized for mass consumption. Frankly, you dont even need the best models for most tasks, and a lot of time you should not use LLMs to orchestrate logical flows at all when you can have testable, verifiable tools to guide them. Look, big picture, this field is the real deal and its developing fast. But we dont need to latest SOTA models to do what 90% of people want to do (talk to their fake AI girlfriend)
This is a really interesting comment. Thanks for writing it.
Did the client send it to you using Fable in the last two days, or was this with an older model?
Also, I heard adoption levels for AI tools like cocounsel/harvey were starting to become significant, are you not seeing that at all in your practice?
These lawyers think they won’t be replaced. Short term? Probably right. Once AI gets the details right, they’re gone.
exactly, lawyers are the one the low hanging replacements for AI. Any document/book heavy/experience heavy knowledge sector is ripe to replacement.
I’m willing to bet a large amount of money that there will be just as many lawyers working in 10 years as there are right now.
This guy's response sounds like "yeah my nephew used Photoshop 5.0 to draw some dinosaurs and it looked like shit, cgi will never replace traditional animation."
“fed to Claude” can mean a lot of things.
Claude has a lot of models and a lot of different effort levels.
If your client was on the free plan then yeah he used a crappy outdated model.
Regardless of what model was used, you must realize that is obviously user error right?
"My best friends child asked an AI to do a thing and it gave a stupid response, AI is useless. "
Networking for the clusters required to train and run these models is also growing incredibly fast. ALAB and MRVL are flying because of it.
Fable is 100% the same as Mythos but it has guardrails built in. If you try to do almost anything cybersecurity related with Fable it reverts back down to Opus 4.8
Not in my field of activity... some stock market research, market overviews, making excel files with charts. Its just little bit faster, but token usage and result quality like Opus 4.6
The Chess test has long been a litmus test for AI, but the ability to find and download a good program, then run it, is not unique to AI. You could have done this too.
Here is what's bullish: Claude can help you write your own analysis software, maybe as simple as a web app. Find stocks you're interested in, plug them into your custom app, and instantly you've got an analysis tailored to your specifications in a way no generalist site can do right now.
This sub should be the definition of Dunning-Kruger
Are you talking about me? I said I personally found it impressive, it represented progress, and it "seems" like it would be bullish for semis, I didn't make any crazy confident claims. I even said in one of the comments I lack any expertise in tech so it's hard for me to evaluate how well model capability can create value for businesses.
The impressive part is not that it used Stockfish, it is that it treated the model as the coordinator instead of the source of truth. That is probably where these systems get useful: knowing when to answer directly, when to call a tool, and when to stop pretending. The semiconductor angle is real, but the bigger shift is workflow demand, because every useful agentic step turns into more compute, more memory, and more infrastructure around the model.
I asked it a question about a chess position
Genuinely how on earth does this relate to stocks?
I explained it in the OP. Possibly the biggest thing limiting AI TAM is its hallucination issues, you can't cut humans out of work flows if AI just makes shit up. In the past AI would've confidently hallucinated a wrong answer to my question. Here, it recognized its limitations, figured out a solution, downloaded a tool on its own, and then gave me a correct answer.
I asked it why it did what it did and it explicitly said that it wasn't confident in its answer without stockfish, so it wanted to make sure it was right. That's self awareness, problem solving, and tool use. To me, it seems like a significant step in the right direction. The key limitation, is that chess is an easier problem for AI than a lot of work tasks.
Doesn't really matter what they asked it about, it was just a test of its capabilities, albeit a somewhat narrow one.