Google DeepMind unveiled JEST.

PLUS: Did Claude kill prompt engineering?


Good morning, human brains, and welcome back to your daily munch of AI news.

Here’s what’s on the menu today:

  • Train AI models 13 times faster 🦾 🤖

    Google DeepMind unveiled JEST.

  • Did Claude kill prompt engineering? 🗣️ 💬

    Anthropic launched features to help you improve your AI apps.

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Peep today's ‘What Would You Do?’ at the bottom. 👇


Train AI models 13 times faster 🦾 🤖

A couple of weeks ago, Google DeepMind unveiled JEST. It’s a new AI training method that's 13 times faster and 10 times more efficient than current methods.

What does it do?

JEST (Joint Example Selection Training) trains AI models using batches of high-quality data. It cuts down on time and energy use.

How does it work?

A small model grades the quality of training data. Then it ranks the data according to quality, and trains a bigger model only using the best data.

Why do I care?

The AI industry needs to generate at least $600 billion a year to pay for its hardware costs. AI models need to be faster and more cost-efficient. Its current state is not sustainable.

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Did Claude kill prompt engineering? 🗣️ 💬

Yesterday, Anthropic launched features powered by Claude 3.5 Sonnet. The goal is to help you improve your AI apps.

What are the features?

Anthropic launched a new Evaluate tab that lets you generate, test, and tweak prompts to get better results.

So, what?

For example, if your app gives answers that are too short, you can use the Evaluate tab to enhance your prompt to get the answers you desire. This could save you tons of time and energy, especially if you’re not a professional prompt engineer.

“It sounds simple, but 30 minutes with a prompt engineer can often make an application work when it wasn’t before.”

Dario Amodei, CEO of Anthropic


Think Pieces 🧠

How much does AI cost to run? The AI industry will need to generate $600 billion a year to pay for hardware spent on AI use.

Startup News 💰

The Chinese video generation tool, KLING, is now generally available. It still requires you to have a Chinese phone number to register.

Research 👨‍🔬

Planetarium — a benchmark that evaluates how well language models can translate natural language instructions into structured planning code.

FunAudioLLM — enhances voice interactions with large language models using SenseVoice for speech recognition and CosyVoice for natural speech generation.


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