Weekly AI and NLP News — February 13th 2023

Here are your weekly articles, guides, and news about NLP and AI chosen for you by NLPlanet!

😎 News and Guides From The Web

• Bard is the Google alternative to ChatGPT. Bard seeks to combine the breadth of the world’s knowledge with the power, intelligence, and creativity of our large language models.

• Google Stock Plunge Erases $100 Billion After Bard Gives Wrong Answer In Ad

• A recap of Google Research in 2022 on Deep Learning.

• Hugging Face releases SpeechT5, a model able to do speech-to-text, text-to-speech, and speech-to-speech.

• A comprehensive list of 100+ products using prompting, divided by category.

• The new Bing and Edge that leverage the power of ChatGPT.

• Understanding Large Language Models: A Transformative Reading List.

• Runway new product Gen-1 uses words and images to generate new videos out of existing ones.

• Dreamix: Video Diffusion Models are General Video Editors.

• New AI features rollng out on Google Maps.

• Announcing the launch of the Medical AI Research Center (MedARC). Work on creating a foundational model in Medical AI.

🔬 Interesting Papers

• What learning algorithm is in-context learning? Investigations with linear models. The authors investigate the hypothesis that transformer-based in-context learners implement standard learning algorithms implicitly.

• A Categorical Archive of ChatGPT Failures. Ten categories of failures, including reasoning, factual errors, math, coding, and bias.

• Toolformer: Language Models Can Teach Themselves to Use Tools.

• The unreasonable effectiveness of few-shot learning for machine translation.

• Large Language Models Are Implicitly Topic Models: Explaining and Finding Good Demonstrations for In-Context Learning. Examining the in-context learning phenomenon through a Bayesian lens, viewing large language models as topic models.

⌨ Interesting Repositories

• AI Expert Roadmap: a set of charts demonstrating the paths that you can take and the technologies that you would want to adopt in order to become a data scientist, machine learning or an AI expert.

• GraphGPT: from natural language to knowledge graphs leveraging large language models.

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