Hendrik Jander

1.3K posts

Hendrik Jander

Hendrik Jander

@hj4nder

Freelance Cloud/Software Architect - Always learning

Katılım Mayıs 2010
1K Takip Edilen56 Takipçiler
Hendrik Jander retweetledi
Bolt Graphics
Bolt Graphics@boltgraphics·
Bring your ideas to life with Zeus, a new type of GPU: - Expandable memory: 32/64/128 GB soldered + 2x/4x SO-DIMM slots for up to 384 GB memory! - Massive improvements to path tracing performance! - 400 GbE QSFP-DD port! - Built-in high-performance RISC-V CPU cores capable of running Linux! - DevKits 2026, Mass Production 2027 And we used the good old 8-pin PCIe power connector that is known to not melt!
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Gary Basin
Gary Basin@garybasin·
if someone at openai or anthropic wants to give me infinite tokens i will make it happen
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Chris Munns
Chris Munns@chrismunns·
My 12+ years at AWS talking with people at companies of all shapes and sizes give me a hot take on this: Most people just never *need* their app to be performant. Nor to scale well. The average enterprise app is a toy. The broad majority of startup software never truly reaches scale. Perf isn’t even measured. The majority of the industry could still sit on a 3-tier app stack forever w/ n+1 redundancy where n=1.
Dmitrii Kovanikov@ChShersh

It blows my mind to realise that in order to write truly performant software, an engineer needs to have a vast span of knowledge ranging from physics and hardware to high-level abstractions and design patterns. It blows my mind even more how the majority ignores all that.

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Simon Willison
Simon Willison@simonw·
@mattyglesias Claude Code turns out to be misnamed: Anthropic thought it was a tool for software developers, it turns out it can help perform any task that can be accomplished by executing commands on a computer
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David Soria Parra
David Soria Parra@dsp_·
Naive tool calling has reached its limits and agents, mcp clients and others need better solutions. We have been listening and releasing a set of new features around tool calling: * Tool Search * Programmatic Tool Calling * Tool Use Examples anthropic.com/engineering/ad…
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Prime Intellect
Prime Intellect@PrimeIntellect·
Introducing the Environments Hub RL environments are the key bottleneck to the next wave of AI progress, but big labs are locking them down We built a community platform for crowdsourcing open environments, so anyone can contribute to open-source AGI
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Erik Meijer
Erik Meijer@headinthebox·
The marble age is over. Melt the wax, or be left behind. I believe that many people that are disappointed in vibe coding have the wrong expectations. They are stuck in the traditional subtractive "coding as marble sculpture" point of view where every line of code you write is like a chisel strike. Mistakes are costly and debugging is like trying to glue chips of marble back on your (apparently not so) perfect sculpture. However, vibe coding is additive, like lost-wax casting. You iterate by melting, bending, and reimagining many possible forms. Errors are cheap and fixing them is very much part of the process. The final result is cast in metal, but only after many cycles of refactoring. Ultimately, like many things in life it all boils down to psychology. ISTJ, INTJ, ESTJ, ISTP ⇒ you probably hate vibe coding since you love control, structure, and plans. ENFP, INFP, ENTP, ENFJ ⇒ you probably love vibe coding since you love big picture, thrive on ambiguity, and open-mindedness. Sorry all of you TODO-list fetishists, the vibe era is here to stay.
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Manveer
Manveer@manveerxyz·
prime intellect masterplan
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John Rush
John Rush@johnrushx·
I've tried all (46 😵‍💫) AI Coding Agents & IDEs [Factory, Cursor, Heyboss, Windsurf, Emergent, Wrapifai, Copilot, Lovable, Bolt, v0, Replit, MarsX, Canva, Devin, Github Spark, IDX, Stitch & more] The most complete list ever made (with demos & notes):
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Jon Chu // Khosla Ventures
Excellent code is a major red flag for early startups. If you're pre pmf, it usually means you aren't moving fast enough and focused on the wrong things i.e. maintainable scalable systems over customer feedback and iteration speed
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Noah MacCallum
Noah MacCallum@noahmacca·
I've been building voice agents for the last 6mo and I think the chat-supervisor pattern is a game changer. Stitched model (STT-LLM-TTS) is slow, but realtime audio models aren't (yet) as smart as text. This has the best of both worlds. Here's how it works:
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Alex Volkov
Alex Volkov@altryne·
Oh this is absolute fire! Can't wait for these models to drop
kyutai@kyutai_labs

Talk to unmute.sh 🔊, the most modular voice AI around. Empower any text LLM with voice, instantly, by wrapping it with our new speech-to-text and text-to-speech. Any personality, any voice. Interruptible, smart turn-taking. We’ll open-source everything within the next few weeks.

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gaut
gaut@0xgaut·
*unmutes* “nothing from my side, thanks”
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Tobias Schmidt
Tobias Schmidt@tpschmidt_·
Tool that I recently discovered and instantly loved: the 𝗔𝗪𝗦 𝗙𝗶𝗻𝗢𝗽𝘀 𝗗𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱 👾 A CLI tool that provides a cost breakdown right in your local CLI. Simple to use and visually appealing. 💛 Thanks, Ravi!
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snimu
snimu@omouamoua·
New blog post:
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OpenAI Developers
OpenAI Developers@OpenAIDevs·
We've made some improvements to Structured Outputs: 🎣 Parallel function calling now works with strict mode—ensuring calls reliably adhere to schema ⚙️ Many more keywords are now supported, letting you specify: - Output string lengths and formats via regex or formats like email - Min/max ranges for numbers - Min/max elements in arrays - and more!
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