Category: News of this week

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AI news of the year 2023 week 52

This week we have big news: a new lawsuit from the New York Times and the public launch of Bing image generator.

The New York times sues Open AI and Microsoft over copyright infringement !

The New York Times sued OpenAI and Microsoft for copyright infringement on Wednesday, opening a new front in the increasingly intense legal battle over the unauthorized use of published work to train artificial intelligence technologies (see here).

”As outlined in the lawsuit, the Times alleges OpenAI and Microsoft’s large language models (LLMs), which power ChatGPT and Copilot, “can generate output that recites Times content verbatim, closely summarizes it, and mimics its expressive style.” This “undermine[s] and damage[s]” the Times’ relationship with readers, the outlet alleges, while also depriving it of “subscription, licensing, advertising, and affiliate revenue.”” (see in The Verge)

This is big news to close the year 2023 as it will create legal instability around the most notorious LLMs (Open AI API is used in most of the start-ups apps and Bing and Office 365 Copilot are the star product of Microsoft for 2024).

As explained in The Verge, The New York Times is one of many news outlets that have blocked OpenAI’s web crawler in recent months, preventing the AI company from continuing to scrape content from its website and using the data to train AI models. The BBC, CNN, and Reuters have moved to block OpenAI’s web crawler as well. […] Axel Springer, which owns Politico and Business Insider, struck a deal with OpenAI earlier this month that allows ChatGPT to pull information directly from both sources, while the Associated Press is allowing OpenAI to train its models on its news stories for the next two years.

Bing image creator is here

Image Creator helps you generate AI images with DALL-E right from the sidebar in Microsoft Edge. Given a text prompt, our AI will generate a set of images matching that prompt. It’s free, there’s no waitlist, and you don’t even need to use Edge to access it. You can use it here. You can read more about it in this article.


We made a comparison between stable diffusion and the Bing image generator using some prompts (the below prompt is an example). In this example the StableDiffusion version is more detailed and fine, but the Bing version really draw what was in the prompt (including rj45 cables). Visually, both are good and allow a good chunk of creativity. Using multiple generators to benefits from all their subtle variations will probably become a common generation method in the future. 

A machine intended to measure a steam engine. The scene is in a steam punk world with many pipes in the background. the machine is connected to a computer network using many colored rj45 links

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AI news of the year 2023 week 51

Hello there, every Monday, find here some news about AI that attracted our attention (and maybe should attract yours too !). This week, we discovered an evaluation of the medical capacities of ChatGPT, covered the launching of now open LLMs from Mitral AI, and a new analysis of Open Models trend that shows a great acceleration of availability for Open Generative AI.

The Stanford Institute for Human-Centered AI tested medical capacities of generative AI (and it is not good …)

AI physicians are not so good …

Stanford Institute for Human-Centered AI, advancing AI research, education, policy, and practice to improve the human condition in an article titled How well do Large Language Models Support Clinician Information Needs show that GPT 4 is not robust enough for use as a medical co-pilot. Using a set of 64 questions from a repository of ~150 clinical questions created as part of the Green Button project, they prompted ChatGPT and measured the quality of the answer. They found that the answers are :

  • Non-deterministic: They found low similarity and high variability in responses to the same question. Jaccard and cosine similarity coefficients were merely 0.29 and 0.45 respectively.
  • Have bad Accuracy: Only 41% of GPT-4 responses agreed with the known answer to medical questions according to a consensus of 12 physicians.
  • Can potentially harm: 7% of answers were deemed potentially harmful by the consensus physicians.

You can read the article here.

Mixtral 8x7b released the 11th of december !

The Mistral teams revealed its last version of Mixtral LLM at Neurips. Mixtral 8x7B is an open-weight mixture of expert models. Mixtral matches or outperforms Llama 2 70B and GPT3.5 on most benchmarks, and has the inference speed of a 12B dense model. It supports a context length of 32k tokens. Mixtral has a similar architecture as Mistral 7B, with the difference that each layer is composed of 8 feedforward blocks. For every token, at each layer, a router network selects two experts to process the current state and combine their outputs. Mixtral has been trained on a lot of multilingual data and significantly outperforms Llama 2 70B on French, German, Spanish, and Italian benchmarks.

Mistral AI is now a major player in the field of generative models. Mistral AI, the French artificial intelligence start-up founded in May 2023 by industry heavyweights, announced on Sunday, December 10 that it had raised €385 million, becoming one of Europe’s two AI champions. The French venture founded by three French AI experts, trained at École Polytechnique and ENS is now valued at some $2 billion. Mistral’s ambitions is to become the leading supporter of the open generative AI community and bring open models to state-of-the-art performance.

AI Open source community is gaining traction and seek to rival private models

Open-source generative artificial intelligence (AI) models are gaining ground, challenging the dominance of centralized cloud-backed models like ChatGPT. Leading players in the generative AI field, such as Google and OpenAI, have traditionally followed a centralized approach, restricting public access to their data sources and training models. research conducted by Cathy Wood’s ARK Invest suggests a potential shift towards open-source AI models outperforming their centralized counterparts by 2024.