🤩Musk’s Big Reveal!

Elon Musk's xAI unveils 'Colossus': the largest AI training system ever

Key Points 

• Colossus is the largest AI training system ever built, surpassing Google's 90,000 GPUs and OpenAI's 80,000 GPUs.

• Developed with Nvidia, Colossus uses cutting-edge H100 GPUs and will soon add H200 models, boosting its power even further.

🚀News - Elon Musk's xAI has launched a powerful new AI training system called 'Colossus'. 

It took the team 122 days of work to successfully get the Colossus 100k H100 training cluster up and running. However, Musk mentioned that they're not stopping there—over the next couple of months, they plan to double its size to 200k by adding 50k H200s to the mix.

🔥What's the buzz about? Colossus is the largest AI training system ever built, already outpacing Google's 90,000 GPUs and OpenAI's 80,000 GPUs and that’s before it even doubles in size. 

Additionally, thanks to being built in partnership with Nvidia, Colossus uses the latest H100 GPUs, with plans to add the new H200 models soon, making it the most powerful AI training system out there.

🕵🏻‍♂️What this means for the industry - Colossus' immense processing power could lead to major advancements in AI fields like natural language processing and complex problem-solving. However, its launch also raises concerns about the concentration of AI power in the hands of a few tech giants and well-funded startups.

Generative AI falls short compared to human summarizers, trial finds

Key Points 

• AI-generated summaries scored 47% on average, significantly lower than the 81% scored by human summaries.

• The AI model struggled with context and relevance, producing "waffly" and redundant summaries that require additional fact-checking.

📒News - According to a trial conducted by Amazon Web Services for the Australian Securities and Investment Commission (ASIC), generative AI doesn’t quite measure up to human summarizers.

The trial, designed to test AI's business potential, found that AI-generated summaries of government documents received an aggregate score of just 47%, while human summaries scored significantly higher at 81%. 

🫢What's more?  The AI model had several issues. It couldn’t provide page numbers for its information, though that might be fixable. More critically, it often missed nuances and context, made confusing choices about what to highlight, and tended to include irrelevant or redundant details. The summaries were also described as "waffly" and "wordy." 

Overall, the AI’s poor performance means that using its summaries might end up requiring more fact-checking, which undermines the supposed benefits of saving time and cutting costs.

🤖In conclusion - If there’s one thing the findings highlight about today’s generative AI, it’s that it’s not a good substitute for human workers.