So many people naively buying into Mythos hype. When it releases (+ spud, Gemini 3.5 etc) to much less hype, there will once again be zero reckoning or apology, and the next cycle will begin
Kennedy canceled $500 million in mRNA research and announced no new mRNA projects will ever be initiated—killing the technology that produced the fastest vaccine rollout in human history.
I have cancer. mRNA technology is already being used to develop some of the next cancer cures. He’s condemning some current and many, many, many future cancer patients to early, preventable deaths.
Kennedy canceled $500 million in mRNA research and announced no new mRNA projects will ever be initiated—killing the technology that produced the fastest vaccine rollout in human history.
This is getting at the fundamental problem with EA, Rationalism etc. They hugely overemphasize the present, which is obviously ironic for long-termism and similar sub-identities of these things people take on.
The short notice thing is the most interesting here to me, like, what does the demo look like for Claude mythos that literally every person who sees it is terrified
In evals, Sonnet with an Opus advisor scored 2.7 percentage points higher on SWE-bench Multilingual than Sonnet alone, while costing 11.9% less per task.
An "internal model at OpenAI" has solved 5 Erdos problems, all reported in the paper below.
All of those have now been listed as Category 1 = Fully AI-generated solutions here:
github.com/teorth/erdos...
OpenAI will release a 'Mythos-class' model in the next few months, e.g. spud, followed by the other labs. Not much will change and all these posters expecting a cyberpunk fantasy to play out will move on to the next wave without blinking
hospital and municipal IT are going to get fucking wrecked whenever someone releases Mythos-class models to the wild and I hope someone in a position to do something about that is on top of it
So many people naively buying into Mythos hype. When it releases (+ spud, Gemini 3.5 etc) to much less hype, there will once again be zero reckoning or apology, and the next cycle will begin
It's kinda wild that the one thing Anthropic claims to focus on, coding/agentic coding, OpenAI beats them at whilst multi-tasking
What Anthropic are actually the best at is marketing. There's an army of people using Claude Code who've never even tried other models or harnesses. Genuinely impressive
The problem with human software developers is that there’s no way to guarantee they’ll write secure code. You just have to *ask them nicely* and hope they do it
Your scheduled “No Kings” events are anticipated by Project 2025.
Trump and the feds permit them ONLY b/c they know these sporadic get-togethers make non-MAGA whites feel like they’re “protesting” Trump’s fascism.
Your No Kings events are not doing anything to stop much less reverse Project 2025.
When a pastor was asked if he's excited for super intelligent AI, he said of course, as being super intelligent it would quickly realise Jesus is lord and become a super Christian.
"Palantir CEO Alex Karp says his AI technology will lessen the power of “highly educated, often female voters, who vote mostly Democrat” while increasing the power of working-class men."
Just saying it right out loud now.
newrepublic.com/post/207693/...
1. Never assume something isn't in the training data. Search the data.
2. Never assume the model is the same as before unless you have access to the weights
3. If you use some else's API, your benchmark isn't private
The White House just posted a video mixing real footage from the Iran strikes with a killstreak animation from Call of Duty: Modern Warfare 3
x.com/WhiteHouse/s...
People really need to call the AI bubble the data centre bubble. It's the financing behind the AI data centres that looks precarious, not the use of the models themselves.
A bit hyperbolic, but I'm getting higher performance on Chinese instruct LLMs than any others. For CoT, where post-training is king (and has trade-offs) there's still a gap.
Not including this person's handle because I don't want to start a big pile-on but there is such a deep media literacy problem on the left. "The New York Times" is not "supporting" any of the things linked; individual writers on their *opinion* pages are making the case for these positions.
‘The world’s top AI models can be prompted to generate near-verbatim copies of bestselling novels, raising fresh questions about the industry’s claim that its systems do not store copyrighted works.’
www.ft.com/content/e4b7...
7. You are likely not doing something original with a model. Facebook 'knows' you were talking about something the same way an LLM often knows the missing context of your code or question.
8. Benchmarks are still modelled after human tests, and are fundamentally flawed for LLMs. Autonomous cars would have passed a driving test almost a decade ago.
‘The world’s top AI models can be prompted to generate near-verbatim copies of bestselling novels, raising fresh questions about the industry’s claim that its systems do not store copyrighted works.’
www.ft.com/content/e4b7...
1. Never assume something isn't in the training data. Search the data.
2. Never assume the model is the same as before unless you have access to the weights
3. If you use some else's API, your benchmark isn't private
4. You have the same biases judging an LLM as any other product. Newer, more expensive or bigger do not mean better
5. You don't know the LLM output was original unless you check.
6. Always check a model's performance on a task multiple times, preferably with superficial variations
New paper on a long-shot I've been obsessed with for a year:
How much are AI reasoning gains confounded by expanding the training corpus 10000x? How much LLM performance is down to "shallow" generalisation (approximate pattern-matching to highly-related training data)?
t.co/CH2vP0Y7OF
Was discussing something like this with a friend last night, but it is fascinating how many parents now and forever take a weird pride in not knowing the basic details of the shows their children enjoy.
The only financial problem major AI companies have is no moat, which *is* existential.
Massive debt, negative gross margin and copyright violations are all tried and true strategies, not problems. Most of the upcoming data center capacity isn't even needed, so a crash won't affect them much either.
SAM ALTMAN: “People talk about how much energy it takes to train an AI model … But it also takes a lot of energy to train a human. It takes like 20 years of life and all of the food you eat during that time before you get smart.”
You only get to say we aren't ready for something if you can describe how to be ready for it, otherwise how do you even know we aren't ready?
Vague fear posting.
also IF the AI doomerism was correct and we are in the process of building literal Skynet the ONLY ethical way forward would be to deploy lethal military violence against the AI industry and it's researchers worldwide.
If you aren't suggesting that, you don't believe this is end-the-world serious.
I understand why people are exhausted by AI hype, and why those of us squarely in the corner of "human dignity uber alles" see AI doomerism as self-serving hype, but I *really* think people on the left broadly need to start thinking seriously about the possibiltiy of the hype being...true.
Epstein will be a trigger word for them, but if you described his actual crimes without the name and fame they would barely have a problem with it. They don't care, and if Epstein was alive he could easily grift his way to influence like Tate and all the others.
this feels like first-time.gif for some people for a new frontier model, so the usual:
- blog posts are marketing. be skeptical
- benchmarks mean less than how it works for *you* on *your* work
- things that lower token spend are good; things that increase it should make you suspect (swarms)
It's very cringe to see people falling for the theatre of moltbook. None of them check or confirm anything. Jingling keys taken at face value yet again.