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

🤖 The job market paradox is real:

📝 67% of job seekers now use AI to write applications
🔍 70% of employers plan AI-only screening (no human oversight)
📈 Employer AI use jumped 428% in just 2 years

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

🧠 @Neural_Nuggets

🎯Google dropped a 68-page prompt engineering guide, here's what's most interesting

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

🧠 @Neural_Nuggets

👁️ Nvidia by the end of 2026 will release a new AI chip Rubin CPX, capable of handling complex tasks such as video and software generation.

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.

🧠 @Neural_Nuggets

🇺🇸 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

Demis argues that it’s nonsense to claim current models are "PhD intelligences”

🧠 @Neural_Nuggets

Legal technology expert's reaction to realizing GPT-4 could replace his professional writing

🧠 @Neural_Nuggets

Microsoft will use Anthropic models to power some features of Office 365 Apps

🧠 @Neural_Nuggets

Google DeepMind CEO Demis Hassabis on AI, Creativity, and a Golden Age of Science | All-In Summit

🧠 @Neural_Nuggets

🔰 Google launched a protocol for AI payments supporting stablecoins in partnership with Coinbase.

🧠 @Neural_Nuggets

Ok should we start worrying

🧠 @Neural_Nuggets

Is this how the uprising begins?

🧠 @Neural_Nuggets

🍼 Mandatory passport data verification will be introduced in ChatGPT — Media

Users under 18 will be automatically switched to "kids mode" with restricted access to sensitive content and AI responses adapted accordingly.

🧠 @Neural_Nuggets

🔰 Google introduced a major Chrome update with new AI features, the browser received:

🔴 Built-in integration with Gemini
🔴 Use of Gemini Nano for fraud detection and protection
🔴 New AI Mode — enhanced search directly from the address bar
🔴 Introduction of “smart agents” that can perform tasks on behalf of the user
🔴 Support for Gems — personal AI assistants that can be customized.

🧠 @Neural_Nuggets

📱 Nvidia intends to invest up to $100 billion in OpenAI.

🧠 @Neural_Nuggets

🫧 Against the backdrop of the news about Nvidia's $100 billion investment in OpenAI, there is a theory circulating online that the biggest market players are essentially cycling capital around, inflating a bubble and profiting from the stock price increase. The scheme looks like this:

1️⃣ OpenAI launches the Stargate project and signs a $300 billion contract with Oracle (the first $100 billion has already been allocated).

2️⃣ Oracle reflects the deal in its financial statements, its shares rise, and Larry Ellison becomes even richer.

3️⃣ Oracle uses this money to purchase graphics cards from Nvidia (a $40 billion contract has already been signed).

4️⃣ Nvidia becomes a leader in market capitalization, and Jensen Huang directs $100 billion back to OpenAI as an investment.

5️⃣ OpenAI's valuation rises, attracting new investors to the company.

Result: money circulates among three corporations, shareholders get richer, and the whole structure relies on the hype around ChatGPT.

🧠 @Neural_Nuggets

🤖 Elon Musk through his company xAI has signed an agreement with the US government — federal agencies will get access to the AI bot Grok and other company models.

The deal with GSA is valid until 2027 and will allow agencies to use Grok in their work under the "Grok for Government" program.

🧠 @Neural_Nuggets