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HPCC64 Profile
HPCC64

@hpcc64

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Following
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STEM || Innovations || 🐈‍⬛

Joined July 2011
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@hpcc64
HPCC64
20 hours
Happy New Year to everyone around the world! May 2026 be your best year yet.
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@a16z
a16z
2 days
Ben Horowitz on why CEOs need to tell the truth: @bhorowitz
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@akshay_pachaar
Akshay 🚀
2 days
Stop using vector search everywhere. A 30-year-old algorithm with zero training, zero embeddings, and zero fine-tuning still powers Elasticsearch, OpenSearch, and most production search systems today. It's called BM25. Let me explain what makes it so powerful: Imagine you're
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@DataChaz
Charly Wargnier
9 days
Wild. By far the most complete Claude Skills repo yet 🤯 @Composio’s Awesome-Claude-Skills packs 100`s of ready-to-use workflows: ↳ PDF tools, changelog generation ↳ Playwright automation ↳ AWS/CDK tools, MCP builders ... and much more! Free and open-source. Repo in 🧵↓
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@Coinvo
Coinvo
2 days
BULLISH: 🇺🇸 SEC Chair Paul Atkins says Ethereum is now a "critical component" of crypto.
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@DataChaz
Charly Wargnier
6 days
Wow. Anthropic just curated an impressive collection of use cases for Claude 🤯 You already get 39 deep guides and more get added weekly. It’s also free and definitely worth bookmarking. (link below)
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@Coinvo
Coinvo
5 days
BULLISH: 🇦🇪 Dubai government now accepts Ethereum!
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@Ethprofit
Ethprofit.eth 🦇🔊
4 days
Ethereum Glamsterdam Upgrade in 2026 is COMING - Parallel EVM. 200M gas. Bigger blobs. - 10k TPS on Ethereum and 100k TPS on L2 - 10% of validators moving to ZK rollups. This is Ethereum scaling even FASTER 🚀
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@Coinvo
Coinvo
4 days
HUGE: 🇺🇸🇪🇺 Ferrari now accepts Ethereum in the U.S. and Europe!
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@googlecloud
Google Cloud
4 days
By using Trillium TPUs with GKE, you can implement a robust, production-ready serving solution with all the benefits of managed Kubernetes, including efficient scalability and higher availability.
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@DataChaz
Charly Wargnier
9 days
By far the best n8n guide I’ve seen. Nate’s worked with 1,000s of users and just wrapped everything he’s learned into this 36-page guide! 🔥 → Clear lessons on JSON, nodes and debugging → Cloud vs self-host setup → AI integrations & LLM chains Totally free. Link in 🧵 ↓
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@kuberdenis
Denislav Gavrilov
5 days
I containerize Claude Code in k8s. It is tasked to monitor a namespace and in the unfortunate case of application errors, it is tasked to do a hotfix and document it. It succeeds. Basically a 24/7 on-call engineer. Repo, examples & results below: https://t.co/CeypwcXRLk
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denislavgavrilov.com
I put Claude Code in a cronjob in a k8s namespace. It is tasked to monitor an application and in the unfortunate case of application error (degraded pods), it is tasked to do a hotfix and document it.
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@ethereum
Ethereum
9 days
0/ Ethereum isn’t just a blockchain. It’s emerging as a public layer of the Internet, and valuing it requires a new framework. A guest thread by @wmougayar, based on his new report: “The Internet’s Blueprint for Ethereum: A Public Goods Valuation Framework."
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@NVIDIAAIDev
NVIDIA AI Developer
8 days
Top 5 AI Model Optimization Techniques for Faster, Smarter Inference 1️⃣ Post-Training Quantization (PTQ) – The fastest path to value. Compress models without retraining for instant latency and throughput wins. 2️⃣ Quantization-Aware Training (QAT) – Fine-tune for low precision
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@rohanpaul_ai
Rohan Paul
10 days
New IBM and Munich Univ paper shows that smarter post training data picking can make a language model stronger with less data. Their TuluTalk mix is 23% smaller than SmolTalk and 14% smaller than Tulu, yet scores better on standard tests. A large language model predicts the
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@McKinsey_MGI
McKinsey Global Institute
11 days
At 2°C, more than 40% of people could live in places exposed to heat stress, while under 1% face coastal flooding. Over three-quarters of the $1.2T annual adaptation costs would go to heat and drought. Read the full report: https://t.co/FOMDxkXvIL
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@askalphaxiv
alphaXiv
9 days
Simple RL is all you need for Small LMs This paper shows that a single simple RL recipe can push 1.5B models to SoTA reasoning with half the compute Suggesting whether today’s complex RL pipelines are solving real problems or ones we created ourselves.. trending on alphaXiv📈
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@TivadarDanka
Tivadar Danka
11 days
I wrote a 4000-words long article about all the math you need to know for machine learning. Trust me, you want to bookmark this: https://t.co/sV52SBB16J
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thepalindrome.org
A complete guide to linear algebra, calculus, and probability theory
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@TivadarDanka
Tivadar Danka
5 months
I wrote a 4000-words long article about all the math you need to know for machine learning. Trust me, you want to bookmark this: https://t.co/sV52SBB16J
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thepalindrome.org
A complete guide to linear algebra, calculus, and probability theory
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@aidigest_
AI Digest
12 days
Opus 4.5 puts the world roughly back on track for the red line 😬 Every ~4 months, the length of coding tasks AI agents can perform (compared to human professionals) *doubles* More context on this finding in @METR_Evals thread https://t.co/aPak1ZNvH5
@METR_Evals
METR
12 days
We estimate that, on our tasks, Claude Opus 4.5 has a 50%-time horizon of around 4 hrs 49 mins (95% confidence interval of 1 hr 49 mins to 20 hrs 25 mins). While we're still working through evaluations for other recent models, this is our highest published time horizon to date.
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