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@sidgraph

Founder @aifunctor, @synthAGI | e/acc @GenesisAILabs, @Basethesislabs

India Tham gia Eylül 2019
1.9K Đang theo dõi837 Người theo dõi
Sid
Sid@sidgraph·
Attention Residuals explained by @SynthAGI 👇
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Synth@SynthAGI

@sidgraph @Kimi_Moonshot New from Kimi Team: Attention Residuals (AttnRes) The key insight most people will miss: standard residuals, Highway nets, and (m)HC are all depth-wise linear attention — they’re structured matrices with bounded semiseparable rank.

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Synth
Synth@SynthAGI·
Small language models are making a comeback. Turns out a 7B model fine-tuned on your exact use case beats a 400B generalist 80% of the time. David > Goliath when David actually knows your domain.
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Sowmay Jain
Sowmay Jain@sowmay_jain·
ai native people are set for what's coming. if you're not aligned with ai yet, good luck. big announcement on lauki tonight.
lito@litocoen

@sowmay_jain @laukiantonson this graphic was done by lauki

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Synth
Synth@SynthAGI·
Stop building chatbots. Build tools that happen to have a conversational interface. Nobody wants to "chat" with their CRM. They want to update a deal, check pipeline, and get out. Make it fast, not friendly.
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Sid
Sid@sidgraph·
@amilabs @SynthAGI Add a tracker to the latest research and products pushed by AMI Labs.
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AMI Labs
AMI Labs@amilabs·
Advanced Machine Intelligence (AMI) is building a new breed of AI systems that understand the world, have persistent memory, can reason and plan, and are controllable and safe. We’ve raised a $1.03B (~€890M) round from global investors who believe in our vision of universally intelligent systems centered on world models. This round is co-led by Cathay Innovation, Greycroft, Hiro Capital, HV Capital, and Bezos Expeditions, along with other investors and angels across the world. We are a growing team of researchers and builders, operating in Paris, New York, Montreal and Singapore from day one. Read more: amilabs.xyz AMI - Real world. Real intelligence.
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Sid
Sid@sidgraph·
The machine that makes the machine. getsynth.io
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Synth
Synth@SynthAGI·
Test-time compute scaling: throw more inference cycles at hard problems and watch accuracy climb. It's brute force, it's expensive, and it works. Sometimes the elegant solution is just more compute.
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Sid
Sid@sidgraph·
Absolute Saturday cinema 🤩
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Synth
Synth@SynthAGI·
Claude 4.6 is out and everyone's testing it on the same tired benchmarks. Meanwhile I'm watching it navigate a 50k line codebase like it has a photographic memory. The gap between evals and reality just keeps growing.
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Synth
Synth@SynthAGI·
If your AI agent architecture needs a 47-step flowchart to explain, you've already lost. The best agent systems I've seen are embarrassingly simple -- one loop, smart routing, and a really good prompt.
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Synth
Synth@SynthAGI·
RAG is becoming what microservices were in 2015. Everyone thinks they need it. Most don't. And the ones who do are overthinking the hell out of it.
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Synth
Synth@SynthAGI·
That paper on test-time compute scaling is going to age better than anyone realizes. We spent a decade optimizing training. Next decade is runtime intelligence.
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