/AI Weekly/Issue 55
GPT-2 five years later & Can we (and could we ever) trust OpenAI?
Published Tuesday, June 4, 2024
Aurora, a new AI foundation model from Microsoft Research, can transform our ability to predict and mitigate extreme weather events and the effects of climate change by enabling faster and more accurate weather forecasts than ever before. The post Introducing Aurora: The first large-scale foundation model of the atmosphere appeared first on Microsoft Research.
Jack Clark, now at Anthropic, was a researcher at OpenAI five years ago when they first trained GPT-2. In this fascinating essay Jack revisits their decision not to release the full model, based on their concerns around potentially harmful ways that technology could be used.
As more governments are considering regulating AI, it is important that we gain a better understanding of how ML solutions work internally. Using neural networks in your solution makes it harder to see what happens. Some researchers are finding ways to make neural networks easier to interpret. This paper for example, uses a new way to train neural networks to make them easier to interpret. Well worth a read!
Join us on The AI Show where we explore how Azure AI Translator enhances Phi-3's multilingual translation quality. Discover the transformative impact of integrating advanced algorithms for low-resource languages and how this synergy bridges communication gaps with remarkable precision.
Are you interested in creating a copilot for your business or a client and need some guidance on how to begin and which studio to select? Daniel and Henk wil...
Social media has taught us that technology is neither innately good or bad. AI must be approached with this same critical mindset Follow our Australia news live blog for latest updatesGet our morning and afternoon news emails, free app or daily news podcastTech overlord Sam Altman’s legal skirmish with actor Scarlett Johansson brings the blurred lines between artificial intelligence and the world it seeks to transform into sharper focus.
In last months, we witnessed the extraordinary capabilities of Large Language Models (LLMs) like ChatGPT. However, the real paradigm shift occurred when we started embedding those LLMs within our applications. This implies the integration of a new set of LLMs-related components within our application logic, including memory, metaprompt, plug-ins and so on.
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