Also, OpenAI is entering the recruitment market: the company is developing a platform for job and candidate search based on AI. The new service is expected to compete with LinkedIn and will launch in mid-2026.
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China's GPU game-changer is here! 🇨🇳
Huawei just dropped the Atlas 300I Duo with 96GB VRAM for under $1,500
Meanwhile NVIDIA's RTX 6000 Pro: $10,000+
This isn't just competition - it's a VRAM revolution for AI/ML enthusiasts who couldn't afford enterprise cards.
The card uses 2x Ascend 310 series chips with LPDDR4X memory - purpose-built for AI inference, not gaming.
Game over for GPU monopoly pricing?🤔
#GPU #AI #VRAM #Tech
🧠 @Neural_Nuggets
Huawei just dropped the Atlas 300I Duo with 96GB VRAM for under $1,500
Meanwhile NVIDIA's RTX 6000 Pro: $10,000+
This isn't just competition - it's a VRAM revolution for AI/ML enthusiasts who couldn't afford enterprise cards.
The card uses 2x Ascend 310 series chips with LPDDR4X memory - purpose-built for AI inference, not gaming.
Game over for GPU monopoly pricing?
#GPU #AI #VRAM #Tech
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Result? Robots talking to robots while humans sit on the sidelines wondering why nobody's getting hired 🤷♂️
Maybe it's time we remembered that behind every resume and job posting is an actual person trying to make a living?
#JobMarket #AI #Hiring
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Read through Google's 68-page paper about prompt engineering. It's a solid combination of being beginner friendly, while also going deeper int some more complex areas.
There are a ton of best practices spread throughout the paper, but here's what I found to be most interesting. (If you want more info, full down down available here)
* Provide high-quality examples: One-shot or few-shot prompting teaches the model exactly what format, style, and scope you expect. Adding edge cases can boost performance, but you’ll need to watch for overfitting!
* Start simple: Nothing beats concise, clear, verb-driven prompts. Reduce ambiguity → get better outputs
* Be specific about the output: Explicitly state the desired structure, length, and style (e.g., “Return a three-sentence summary in bullet points”).
* Use positive instructions over constraints: “Do this” >“Don’t do that.” Reserve hard constraints for safety or strict formats.
* Use variables: Parameterize dynamic values (names, dates, thresholds) with placeholders for reusable prompts.
* Experiment with input formats & writing styles: Try tables, bullet lists, or JSON schemas—different formats can focus the model’s attention.
* Continually test: Re-run your prompts whenever you switch models or new versions drop; As we saw with GPT-4.1, new models may handle prompts differently!
* Experiment with output formats: Beyond plain text, ask for JSON, CSV, or markdown. Structured outputs are easier to consume programmatically and reduce post-processing overhead .
* Collaborate with your team: Working with your team makes the prompt engineering process easier.
* Chain-of-Thought best practices: When using CoT, keep your “Let’s think step by step…” prompts simple, and don't use it when prompting reasoning models
* Document prompt iterations: Track versions, configurations, and performance metrics.
#PromptEngineering #AI
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It will be the successor to the Blackwell architecture and will combine all stages of data processing directly on the chip.
According to the company’s estimates, investments of $100 million in such systems could bring up to $5 billion in revenue.
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🇺🇸 Elon Musk stated that without the involvement of artificial intelligence and robotics in solving the US national debt problem, the country could be on the brink of collapse.
According to him, interest payments on the debt have already exceeded Pentagon spending, which threatens the stability of the entire economy.
🧠 @Neural_Nuggets
According to him, interest payments on the debt have already exceeded Pentagon spending, which threatens the stability of the entire economy.
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Legal technology expert's reaction to realizing GPT-4 could replace his professional writing
🧠 @Neural_Nuggets
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YouTube
Google DeepMind CEO Demis Hassabis on AI, Creativity, and a Golden Age of Science | All-In Summit
(0:00) Introducing Sir Demis Hassabis, reflecting on his Nobel Prize win
(2:39) What is Google Deepmind? How does it interact with Google and Alphabet?
(4:01) Genie 3 world model
(9:21) State of robotics models, form factors, and more
(14:42) AI science breakthroughs…
(2:39) What is Google Deepmind? How does it interact with Google and Alphabet?
(4:01) Genie 3 world model
(9:21) State of robotics models, form factors, and more
(14:42) AI science breakthroughs…
Google DeepMind CEO Demis Hassabis on AI, Creativity, and a Golden Age of Science | All-In Summit
🧠 @Neural_Nuggets
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Users under 18 will be automatically switched to "kids mode" with restricted access to sensitive content and AI responses adapted accordingly.
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