TechMD

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TechMD

TechMD

@TechMDAI

🔬 MD fueled by a deep passion for Medicine & Tech. 🌐 Exploring the frontiers of VR/AR/MR & BCI. 🤖 AI enthusiast.

Beigetreten Haziran 2023
3.5K Folgt648 Follower
Matthew Berman
Matthew Berman@MatthewBerman·
Running a fine-tune on Qwen3.5-35B-A3B using @UnslothAI It's ALIIIIIVEEE
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Awni Hannun
Awni Hannun@awnihannun·
I joined Anthropic as a member of the technical staff. Excited to work on frontier modeling at a place with unwavering values and a generational mission.
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Alican Kiraz
Alican Kiraz@AlicanKiraz0·
Isı sorununu çözdüm🔥🦾
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Lotto
Lotto@LottoLabs·
I thought it was the golden age of LLMs BEFORE agents and qwen3.5
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Andrew Ng
Andrew Ng@AndrewYNg·
New course: Agent Memory: Building Memory-Aware Agents, built in partnership with @Oracle and taught by @richmondalake and Nacho Martínez. Many agents work well within a single session but their memory resets once the session ends. Consider a research agent working on dozens of papers across multiple days: without memory, it has no way to store and retrieve what it learned across sessions. This short course teaches you to build a memory system that enables agents to persist memory and thereby learn across sessions. You'll design a Memory Manager that handles different memory types, implement semantic tool retrieval that scales without bloating the context, and build write-back pipelines that let your agent autonomously update and refine what it knows over time. Skills you'll gain: - Build persistent memory stores for different agent memory types - Implement a Memory Manager that orchestrates how your agent reads, writes, and retrieves memory - Treat tools as procedural memory and retrieve only relevant ones at inference time using semantic search Join and learn to build agents that remember and improve over time! deeplearning.ai/short-courses/…
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Andrej Karpathy
Andrej Karpathy@karpathy·
Thank you Jensen and NVIDIA! She’s a real beauty! I was told I’d be getting a secret gift, with a hint that it requires 20 amps. (So I knew it had to be good). She’ll make for a beautiful, spacious home for my Dobby the House Elf claw, among lots of other tinkering, thank you!!
NVIDIA AI Developer@NVIDIAAIDev

🙌 Andrej Karpathy’s lab has received the first DGX Station GB300 -- a Dell Pro Max with GB300. 💚 We can't wait to see what you’ll create @karpathy! 🔗 #dgx-station" target="_blank" rel="nofollow noopener">blogs.nvidia.com/blog/gtc-2026-… @DellTech

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Saint Nomad
Saint Nomad@Saint_n0mad·
Literally Vision Pro is one of the most underrated Apple product of all times AI hype has totally overshadowed the potential of AR technology but potential is still there AR is the future.
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Matthew Berman
Matthew Berman@MatthewBerman·
First full test: 103 t/s * Nemotron 3 Super (Q4) * LMStudio w/ LM Link Plenty of headroom. Going to try to leverage NVFP4 to get max speed.
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Rongwei Ji
Rongwei Ji@rongweiji1·
new project trying the Alpamayo , reasoning for the autonomous v scene. and on edge device the DGX Spark-----GTC 2026 hackathon project
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Ahmad
Ahmad@TheAhmadOsman·
the state of AI
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Ray Fernando
Ray Fernando@RayFernando1337·
Dell Pro Max with GB300 + 748Gb unified memory. GPU go burrrrrrrr @MichaelDell plz send one for NemoClaw and local AI livestream testing. 🤝
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TechMD
TechMD@TechMDAI·
@yacineMTB Only limit I hit was the rate limit
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kache
kache@yacineMTB·
I have found the limits of gpt 5.4
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clem 🤗
clem 🤗@ClementDelangue·
We just released an hf CLI extension to detect the best model/quant for a user's hardware and then spins up a local coding agent. Time to go local/private/free/fast for your agents thanks to open-source!
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TechMD
TechMD@TechMDAI·
@digitalix Do you think it has any performance Enhancements
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TechMD
TechMD@TechMDAI·
Really liking the the quality of life improvements to the NVIDIA Sync app. Especially the tailscale implementation #DGXSPARK #NVIDIA
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thecollabagepatch
thecollabagepatch@thepatch_kev·
i was very bummed about some things in october when we first got it generation time was really poor with all the audio models i use, but since then me and claude have hyper optimized it so that it beats the T4 on every audio task i give it. i can also train models while i keep this docker compose network active lol i'm very happy i went with it over the m4. it's also so nice that it's not my laptop so i can just keep it running experiments while i do other stuff
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thecollabagepatch
thecollabagepatch@thepatch_kev·
things a dgx spark lets me do sry jeff idk if we need you anymore
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