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Happy Friday Big Brainiacs,

Yesterday was a busy day for me. I traveled back to Texas and the one and only Elon Musk responded to one of my tweets!

Stay tuned for a future edition where I will break down Meta’s plan to use Threads as a new data source for their AI models.

Now for today’s topics…

Today's AI spotlights:

• Tech titans tango with China’s AI market 🤖

• OpenAI gets serious about AGI 🧠

• Can decentralized computation actually work? 🤔

We’re about to start pumping out more videos on our Instagram. Check us out!

🤖 TECH TITANS TANGO WITH CHINA’S AI MARKET

AI powerhouses and tech CEOs met up in Shanghai for the World Artificial Intelligence Conference.

Everyone wants a piece of China's AI pie, including Tesla's Elon Musk who showed off a bipedal robot and hinted at partnerships with Chinese automakers.

Microsoft, Google, and other American firms are working hard to enter China's AI ecosystem, despite stringent internet regulations and growing U.S.-China tech tensions.

Beijing's ban on certain chips and potential restrictions on AI content add to the complications. Yet, the $26.4 billion forecasted value of China's AI market by 2026 is too tempting to ignore. Tech ethics and the risk of being implicated in espionage add another twist. Watch this space!

📰 Full Article Here

🧠 OPENAI GETS SERIOUS ABOUT AGI

OpenAI's co-founder Ilya Sutskever is spearheading a new team.

Its mission? Prevent Skynet (a la Terminator) from becoming reality.

The so-called Superalignment Team believes human-level AI could be here this decade. But there's a slight problem: we don't know how to control it yet.

So what solutions are they looking at? Train AI to manage other AI, which is about as meta as it gets.

OpenAI knows it's not foolproof, and the hardest parts might not even be technical. Still, they're giving it a shot.

The goal is to make sure that none of the AI-doom n’ gloomers' worst fears reach close to reality.

📰 Full Article Here

🤔 CAN DECENTRALIZED COMPUTATION ACTUALLY WORK?

Blockchain and AI: can they play well together?

Some certainly think so, especially when it comes to decentralized computation. However, there are many hurdles to get past before this is possible.

Some research from Together though looks promising. Specifically, it aims to solve the communication bottleneck between GPUs.

The goal? Enabling large-scale model training on slow networks. Even when the network's 100x slower, they only see a 1.7-2.3x drop in throughput.

In fact, their system is 4.8x faster than Megatron and DeepSpeed in a geo-distributed setting.

Other endeavors include tackling fault tolerance, training algorithms, and security.

📰 Full Article Here

📰 OTHER HEADLINES & STORIES

• Microsoft launches free AI training as enterprises grapple with skills shortage

• Big tech companies want AI regulation — but on their own terms

• Mining Companies Consider Repurposing Idle GPUs to HPC and AI Markets

• The Human Labor Powering AI Engines

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💼 AI JOBS

• Compliance Analyst for Grindr

• AI Content Writer for DataAnnotation

• Technology Product Counsel - AI/ML for Proventia Law

• Conversational AI Developer for IntelePeer

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🖼️ AI ART PIECE

Dream Reading Dens — u/ladyname

🤖 CHATGPT PROMPT OF THE DAY

Not sure what this means, but it can’t be good…🫣