Product Engineer @ pixelwisdom.ca | Clients include @arcprize & @juliarturc Musician • Polyglot • Proud dad
Québec, Canada
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Philippe Tremblay retweeted
Likely that 50%-80% of people never pay for AI.
Cognitive gap between the people who embrace it into their daily thinking vs those who opt out is going to be insane
Like 70iq talking to 170iq
This trend began as people built information diets via social media that give them an edge, which you can literally see. Tech X is months of not years ahead of the curve.
But AI accelerates that dramatically.
Being tapped into the global intelligence machine is going to make people super smart and super weird
98% of US households aren't paying for AI yet
More charts in State of Markets II: a16z.news/p/state-of-markets…
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"There's never been a "used third party assets and plugins" disclosure policy." Good point!
It's the stigma.
Everyone's decided games are too holy to let AI touch them.
Steam has an AI disclosure policy, stupidly.
Developers are genuinely scared to touch AI, others use it in unnecessarily limited ways.
I'm an indie game dev in my spare time and even I, ceo of an AI startup, won't be using AI in game development for the foreseeable future because I don't want to get into shit with steam. If disclosure wasn't mandatory, my stance is that it's no one's business what tools I use in my creative process as long as I put stuff out there that genuinely reflects my creative vision.
There's never been a "used third party assets and plugins" disclosure policy.
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Gemini 4 Argon is the new #1 on APEX-Agents.
82.2% Pass@1 (#1)
87.9% Mean score (#1)
It is the first model to exceed 80% Pass@1. It is +6.7 pts over the prior #1, Sonnet 5.5, and +14.4 pts over the best prior model from DeepMind, Gemini 3.7 Flash (67.8%).
#𝟭 𝗶𝗻 𝗮𝗹𝗹 𝗔𝗣𝗘𝗫-𝗔𝗴𝗲𝗻𝘁𝘀 𝗱𝗼𝗺𝗮𝗶𝗻𝘀
Google says Argon delivers frontier performance in "enterprise knowledge work like legal and finance." On APEX-Agents, Gemini 4 Argon ranks first in every professional domain.
Management consulting: 90.3% (#1)
Investment banking: 80.9% (#1)
Corporate law: 75.3% (#1)
Consulting appears to be Argon's strongest domain, scoring 10.3 pts ahead of Opus 5.5. It is also the first model to score above 90% on any APEX-Agents leaderboard.
𝗧𝗼𝗸𝗲𝗻 𝘂𝘀𝗮𝗴𝗲 𝗯𝘆 𝗔𝗣𝗘𝗫-𝗔𝗴𝗲𝗻𝘁𝘀 𝗱𝗼𝗺𝗮𝗶𝗻
Argon used 2.6M tokens per attempt on average. The median attempt used 1.75M.
Investment banking: 3.5M per attempt
Corporate law: 2.7M
Management consulting: 1.7M
Almost all Gemini 4 Argon’s token usage comes from input. It used 2.61M input tokens per attempt compared with only 28.5K output tokens per attempt.
That is about 90 input tokens for every output token. The agent reads a lot of files before composing a short answer.
Congrats to @Google and @GoogleDeepMind.
See full leaderboard: mercor.com/apex/apex-agents-…
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Philippe Tremblay retweeted
"No man ever runs an experiment on the same infra twice, for it's not the same infra and he's not the same man." - Heraclitus
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Philippe Tremblay retweeted
It took me 4 hours or so in ultrafast to go througha 500 sub + 62,500 tokens.
😭
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Philippe Tremblay retweeted
Claude Opus 5.5 wrote the piano music in Python, created the 3D animation in Python, and rendered it in Blender.
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Pushing the blade in further I see.
GPT-6.1 Sol is our most demanded model pretty much ever both across both the API and subscriptions.
Within ChatGPT & Codex, we were under heavy load, but have brough more capacity online and the speed should get much better in the coming hours, reaching almost twice the speed compared to what we served yesterday.
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Gemini 4 Argon built 30 Vibe Code Bench apps perfectly.
That's more than any other model. Claude Opus 5 is next with 25, then GPT-6 Astra with 24.
It built 30 Vibe Code Bench apps perfectly, more than any other model, up from 16, with a third fewer tool calls. Claude Opus 5 is next with 25, then GPT-6 Astra with 24.
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Lots of discussion out there about our next model(!), so I wanted to give an early look as soon as possible. Introducing Gemini 4 Argon!
It shows frontier performance in complex workflows, cyber defense and software engineering. Teams are using it extensively at Google, from coding to quantum computing, great feedback.
Here’s a look at the benchmarks:
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