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Hey ,

Welcome to this week's edition of AlphaSignal the newsletter for AI experts.

Whether you are a researcher, engineer, developer, or data scientist, our summaries ensure you're always up-to-date with the latest breakthroughs in AI.

Let's get into it!

Lior

📑 RELEASES & ANNOUNCEMENT

1. Google AI Launches a Free Learning Path on Generative AI
The new course will guide you through a curated collection of content on Generative AI products and technologies, from the fundamentals of Large Language Models to how to create and deploy generative AI solutions on Google Cloud.

2. Top AI researchers and CEOs warn against ‘risk of extinction’ in 22-word statement
It’s another high-profile warning about AI risk that will divide experts. Signatories include Google DeepMind CEO Demis Hassabis and OpenAI CEO Sam Altman.

3. Andrew NG Releases 3 New Generative AI course
The new course includes:
- Building Systems with the ChatGPT API
- LangChain for LLM Application Development
- How Diffusion Models Work

4. OpenAI is Pursuing a New Way to Fight A.I. ‘hallucinations’
OpenAI’s potential new strategy for fighting the fabrications: Train AI models to reward themselves for each individual, correct step of reasoning when they’re arriving at an answer, instead of just rewarding a correct final conclusion.

5. Marc Andreessen Just Published A New Post Titled: “Why AI Will Save the World”
The era of Artificial Intelligence is here, and boy are people freaking out.
Fortunately, I am here to bring the good news: AI will not destroy the world, and in fact may save it.

^NEWS
The Top Performing LLM Goes Open Source: Falcon 7B/40B 🦅

The Technology Innovation Institute (TII) has just unveiled their groundbreaking Falcon LLM series of large language models. These models, Falcon-40B and Falcon-7B, are now available under the Apache 2.0 license, with all royalties and commercial usage restrictions waived. What makes them stand out? Well, let me break it down for you.

Falcon LLM leverages a unique architecture and data pipeline. It has been trained on a massive web dataset called RefinedWeb, which combines public web crawls with carefully curated sources like research papers and social media conversations. This blend allows the models to achieve exceptional performance, surpassing many other models on NLP benchmarks.

Now, let's talk numbers. Falcon-40B and Falcon-7B boast a staggering 40 billion and 7 billion parameters respectively. These large-scale models excel in natural language understanding and generation. Their autoregressive decoder-only design, coupled with extensive training, makes them perfect for a wide range of applications. What's particularly fascinating is that Falcon LLM's efficient architecture enables impressive performance while reducing training compute budgets. It's a win-win for AI researchers and engineers like us.

Want to promote your company, product, job, or event to 100,000+ AI researchers and engineers? You can reach out here.

^NEWS
Europe Wants Platforms To Label AI-Generated Content To Fight Disinformation

The European Union is urging signatories to its Code of Practice on Online Disinformation to label deepfakes and other AI-generated content. Vera Jourova, the EU's values and transparency commissioner, emphasized the need for technology to recognize AI content and clearly label it for users. The current version of the Code does not include provisions for identifying and labeling deepfakes, but the Commission aims to change that.

Two discussion angles are being considered: one focuses on services integrating generative AI, which should incorporate safeguards against disinformation; the other requires signatories with services that can disseminate AI-generated disinformation to implement technology for recognizing and labeling such content. Jourova revealed that Google has technology to detect AI-generated text content and is working to improve it.

The Commission wants platforms to implement labeling immediately and expects action on reporting AI-generated disinformation risks next month. The Code currently has 44 signatories, including major tech companies. Twitter recently withdrew from the voluntary Code, potentially inviting enforcement action under the legally binding Digital Services Act. Jourova also raised concerns about Russia's disinformation efforts, election security, fact-checking, and access to data for researchers.

🤖 TOP OF REDDIT

Japan Goes All In on AI: Japan’s government recently reaffirmed that it will not enforce copyrights on data used in AI training
↑ 1829

AI hypocrisy: OpenAI, Google and Anthropic won't let their data be used to train other AI models, but they use everyone else's content
↑ 1477

White House is no longer laughing at AI Risk, like they were months ago.
↑ 1229

I Created an AI Basketball Referee [P]
↑ 1132

The proper use of Generative Fill
↑ 1110

^NEWS
OpenAI Releases Their Own Guide To Optimize GPT

The article provides valuable insights and practical tips to optimize the performance of GPT models, enabling users to achieve better results. It emphasizes the importance of clear instructions when interacting with GPTs, highlighting the need to provide specific details, request desired writing styles, and use delimiters and step-by-step instructions for tasks. The article also recommends providing examples and specifying the desired length of outputs to guide the model effectively.

Snippet
Write clear instructions:

• Include important details in your query to receive more relevant answers.

• Ask the model to adopt a specific persona or writing style.

• Use delimiters to clearly indicate different parts of the input.

• Specify the steps required to complete a task.

• Provide examples to demonstrate the desired output.

• Specify the desired length of the output.

• Provide reference text to help the model generate accurate answers.

Thank You

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