Tim Michaud
1.2K posts

Tim Michaud
@TimGMichaud
Founder @ New thing - (YC Alum) still a Security Nerd.
Middle of Freakin Nowhere Katılım Mart 2012
923 Takip Edilen1.3K Takipçiler

Thinking effort doesn't fix hallucination.
Even the best frontier model at matched HIGH still gets 24.2% of fields wrong on adversarial insurance docs. Going from default to HIGH buys 0-2pp per model.
aginor.ai/extraction-tes…

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What makes this different: the generator emits the rendered document AND the ground-truth JSON in the same pass. No annotation step. Ground truth is authoritative by construction.
Full writeup, raw outputs, repo, 25-doc sample packet:
aginor.ai/extraction-tes…
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Tim Michaud retweetledi

I’m #hiring an individual contributor for a fully remote, global role at the intersection of vulnerability research, exploit development, and ML/AI — with a focus on fine-tuning open-weight #LLMs. 🧠
I’m not looking for an “LLM whisperer” or an “LLM pilot.” 🚫
I’m looking for someone who deeply understands post-training, data, evaluation, and how to make models reliable in real-world environments. 🔐
The application link is in the first comment. 🌍
#Hiring #LLM #AI #ML #FineTuning #CyberSecurity #llmwhisperer #llmpilot
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@GergelyOrosz Yeah I had this turn off on me before; SUPER annoying cause it's not obvious that it's off (or on!) :|
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@b1ack0wl Started a few companies (2 boot strapped 1 VC backed, new one bootstrapped but will very likely go raise) - happy to chat about it if it helps!
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I did some light homework into this and it's a very risky move with a high degree of failure
I would have to start with the following:
* Figure out a name and register it
* Register an LLC
* Come up with a business plan + portfolio
* Obtain a SMB loan
* Figure out the rest
b1ack0wl@b1ack0wl
ngl I think about this every so often. after decades of looking at embedded, mobile, cloud, windows (userland), and linux (userland+kernel) I feel like I have a foundation to create something of my own. but at the same time throwing myself at a high risk idea is a bit spooky
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I think this is a mix of what @susantejuosho (x.com/susantejuosho/…) said, and also the changing demographic. YC used to target "older" founders who were used to the way things worked at big companies; the "you can just do things"/"go fast"/"do things that don't scale" was to help re-orient people from how things worked at big tech. But as they start having younger and younger people join, who do not have that context, the messaging is heavily muddled and distorted.
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New video: Y Combinator lets you cross the line.
The adults in the room aren't going to stop you from doing something seriously wrong. Young founders need to be aware of that.
youtube.com/watch?v=ptT_LG…

YouTube

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@GergelyOrosz Happened to us last year; was such a PITA we ended up cancelling.
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@HackingDave Honestly if 5.5 is an improved 5.3xhigh I think we might see a switch back towards OAI.
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I understand there’s a ton of Claude fans out there. I was there too 4-5 weeks ago. Then it got way way way worse and without explanation.
What’s worse is that I would consider myself a heavy power user. What about the folks that aren’t and have no idea it was dumbed down over 60% or more since its initial release and are using this day to day.
Codex is outperforming Claude in every way right now. Additionally OpenAI is much more transparent, cheaper, and produces much better code in every way to Claude at the moment.
Claude has massive outages, lack of transparency to users, some really bad operational and security practices.
They’ve lost me. I’m done.
What happened ?
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@thefineprintesq Oh that's interesting; thanks for the info :)!
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@TimGMichaud My brother in Christ, hell no. Every big law firm thinks it’s reinvented the wheel. Surprise, clients share it with their other firms and it cycles into a fairly amorphous market template. Some firms have decent data, but it gets swallowed up by the same
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I think a lot of people are letting contexts grow too close to 300k+ tokens which is where capabilities start to drop off; but I think there's a good chance there is a "I built my early project on AI and it was FAST; it's now way more complex", and therefore giving them more issues that add further complexity
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@spiritbuun Forcibly setting the effort level + forcing compaction well before 300k tokens and using subagents for many things has definitely kept things closer to how they used to be.
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@MartinGTobias Latency I think is the bigger win for SLMs, and as companies have better data (or buy it) to train the models why rely on a third party when your own model is better/faster/cheaper.
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