‘Starfield’ Dev Bethesda Just Lost Peter Hines, One of Its Most Important Executives
After 24 years with the company and the launch of Starfield, Peter Hines, Bethesda’s head of publishing, is leaving.
A method to interpret AI might not be so interpretable after all
As autonomous systems and artificial intelligence become increasingly common in daily life, new methods are emerging to help humans check that these systems are behaving as expected. One method, called formal specifications, uses mathematical formulas that can be translated into natural-language expressions. Some researchers claim that this method can be used to spell out decisions …
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Scam artists have realized they can throw together a fake online store, put up a bunch of AI-generated images of fantastical (but fake) products, sell them for a dumb price that makes no sense considering what it would cost to actually produce them & then take your money & your credit card and run.
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Adam & Eve
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Testing animatediff + qr code monster
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Batch calibration: Rethinking calibration for in-context learning and prompt engineering
Posted by Han Zhou, Student Researcher, and Subhrajit Roy, Senior Research Scientist, Google Research Prompting large language models (LLMs) has become an efficient learning paradigm for adapting LLMs to a new task by conditioning on human-designed instructions. The remarkable in-context learning (ICL) ability of LLMs also leads to efficient few-shot learners that can generalize from …
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Shift from proactive to predictive monitoring: Predicting the future through observability
In today’s fast-paced digital landscape, the seamless operation and performance of software applications is crucial for businesses. Downtime, glitches and service interruptions can result in significant revenue loss and damage a company’s reputation. This is where modern, advanced monitoring solutions like IBM Instana come into play. With its cutting-edge capabilities, Instana goes beyond traditional monitoring …
Batch calibration: Rethinking calibration for in-context learning and prompt engineering
Posted by Han Zhou, Student Researcher, and Subhrajit Roy, Senior Research Scientist, Google Research Prompting large language models (LLMs) has become an efficient learning paradigm for adapting LLMs to a new task by conditioning on human-designed instructions. The remarkable in-context learning (ICL) ability of LLMs also leads to efficient few-shot learners that can generalize from …
Read more “Batch calibration: Rethinking calibration for in-context learning and prompt engineering”
Google adds AI image generation to Search — but there’s a catch
The new feature is available only for those who have already opted into Google Search Labs, the company’s experimental beta testing service.Read More
Scientists begin building AI for scientific discovery using tech behind ChatGPT
An international team of scientists, including from the University of Cambridge, have launched a new research collaboration that will leverage the same technology behind ChatGPT to build an AI-powered tool for scientific discovery.