Cold Takes

FEBRUARY 10, 2023

Let’s say you’re convinced that AI could make this the most important century of all time for humanity. Most of today’s opportunities are concentrated in the US and UK, where the biggest AI companies (and AI-focused nonprofits) are. This may change down the line.

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O'Reilly Media

JUNE 7, 2022

Not so many years ago, one problem with AI was that AI systems were only good at one thing. After IBM’s Deep Blue defeated Garry Kasparov in chess, it was easy to say “But the ability to play chess isn’t really what we mean by intelligence.” A model that plays chess can’t also play space wars.

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Cold Takes

JANUARY 25, 2023

In the most important century series, I argued that the 21st century could be the most important century ever for humanity, via the development of advanced AI systems that could dramatically speed up scientific and technological advancement, getting us more quickly than most people imagine to a deeply unfamiliar future.

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Cold Takes

DECEMBER 22, 2022

In previous pieces, I argued that there's a real and large risk of AI systems' developing dangerous goals of their own and defeating all of humanity - at least in the absence of specific efforts to prevent this from happening. In this minefield, a single mine is big enough to endanger all the racers.)

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Marktechpost

JUNE 7, 2023

Some industry insiders claim that the most useful applications of artificial intelligence in video games are the ones that go under the radar. Each kind of game will use AI in its unique way. AI programs the non-playable characters’ responses and behaviors. AI dominates this survival game.

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AWS Machine Learning Blog

SEPTEMBER 6, 2023

Today, we are excited to announce the capability to fine-tune Llama 2 models by Meta using Amazon SageMaker JumpStart. Fine-tuned LLMs, called Llama-2-chat, are optimized for dialogue use cases. Generative AI foundation models have been the focus of most of the ML and artificial intelligence research and use cases for over a year now.

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The MLOps Blog

MAY 9, 2023

If all goes well, of course ? It is used to streamline, orchestrate, and automate the machine learning workflow within the ML platform. One of the most prevalent complaints we hear from ML engineers in the community is how costly and error-prone it is to manually go through the ML workflow of building and deploying models.

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