https://t.co/b774dXzDJ7 https://t.co/NeC9DfB4rI
— Aravind Srinivas (@AravSrinivas) 28 mai 2026
Perplexity Computer can now help prepare your federal tax return. Select “Navigate my taxes” on Computer to give it a shot.
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https://t.co/b774dXzDJ7 https://t.co/NeC9DfB4rI
— Aravind Srinivas (@AravSrinivas) 28 mai 2026
Perplexity Computer can now help prepare your federal tax return. Select “Navigate my taxes” on Computer to give it a shot.
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Why does this matter for AI inference specifically? Training = throughput problem. Inference = latency problem. When a user talks to an AI assistant, tokens have to return fast. Latency, memory access, bandwidth, and interconnect all matter, not just raw compute. In large AI
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They're toy models at best When I say that, I mean literal toys, like the one you buy your kids 10 years down the road, small models will be in these toys on similar cheap hardware, but IT IS NOT the next big play
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Please stop pitching me hardware startups that are tightly coupled with models No, printing model architectures on hardware isn't smart, it's a waste of PCBs and memory GTX 1080s from 10 years ago could run today's models, but a model on a PCB today won't be used in 10 years
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Web designers after reading this: https://t.co/yONuEtjT8L pic.twitter.com/p3y16ldruL
— Charly Wargnier (@DataChaz) 27 mai 2026
Web designers after reading this:
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You should read this thread.
— NVIDIA AI (@NVIDIAAI) 27 mai 2026
It used to take about 25 seconds to generate a 5-second video on 8 Blackwell GPUs. The legends at @haoailab brought that down to just 4.2 seconds on a single Blackwell GPU… and then open sourced the tech behind it. https://t.co/egQnhx0N1e
You should read this thread. It used to take about 25 seconds to generate a 5-second video on 8 Blackwell GPUs. The legends at @haoailab brought that down to just 4.2 seconds on a single Blackwell GPU… and then open sourced the tech behind it.
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Every AI response depends on more than compute. It also depends on: Memory access speed Interconnect efficiency Chip-to-chip communication overhead Data movement costs End-to-end system latency When any of these slow down, your AI gets slower and more expensive. The model
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Introducing Runway MCP. Now you can connect Runway directly into Claude, ChatGPT, Cursor, Replit and more.
— Runway (@runwayml) 27 mai 2026
Generate polished images and videos with state-of-the-art models, like Gen-4.5, Seedance 2.0, GPT Images 2.0, Kling and more. Right from where you're already working.… pic.twitter.com/J3wBb4kZDy
Introducing Runway MCP. Now you can connect Runway directly into Claude, ChatGPT, Cursor, Replit and more. Generate polished images and videos with state-of-the-art models, like Gen-4.5, Seedance 2.0, GPT Images 2.0, Kling and more. Right from where you're already working.
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PULLING OUT YOUR PHONE TO RECORD A CHAT IS AWKWARD@bluedot_ai just completely solved this with their new Apple Watch app.
— Charly Wargnier (@DataChaz) 27 mai 2026
The magic?
It connects seamlessly to Claude.
So you can instantly query months of convos/meetings like a database 🤯pic.twitter.com/Q0vbf4AH3D https://t.co/Uw7qJ8bGg2
PULLING OUT YOUR PHONE TO RECORD A CHAT IS AWKWARD @bluedot_ai just completely solved this with their new Apple Watch app. The magic? It connects seamlessly to Claude. So you can instantly query months of convos/meetings like a database

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Huawei’s Tau Scaling signals a broader shift for semiconductors: progress may depend less on nanometers alone and more on latency, data movement, energy efficiency, and coordinated system design. Beyond shrinking, the next frontier is orchestration.