AI isn’t the problem — rushing it into the wrong tasks without the right data, expertise or guardrails is what makes projects fall apart.
Morning Overview on MSN
AI model cracks yeast DNA code to turbocharge protein drug output
MIT researchers have built an AI language model that learns the internal coding patterns of a yeast species widely used to manufacture protein-based drugs, then rewrites gene sequences to push protein ...
SeaCast is an innovative high-resolution forecasting system for the Mediterranean that harnesses AI to deliver faster and ...
Industrial yeasts are a powerhouse of protein production, used to manufacture vaccines, biopharmaceuticals, and other useful compounds. In a new study, MIT chemical engineers have harnessed artificial ...
AOMedia AV2 video codec draft specification release, and a quick try at the reference implementation
After 5 years of work and over 2700 commits against the reference software, the Alliance for Open Media (AOMedia) has recently released the AV2 specification. This next-generation open video codec ...
Abstract: Address event representation (AER) object recognition task has attracted extensive attention in neuromorphic vision processing. The spike-based and event-driven computation inherent in the ...
Why was a new multilingual encoder needed? XLM-RoBERTa (XLM-R) has dominated multilingual NLP for more than 5 years, an unusually long reign in AI research. While encoder-only models like BERT and ...
Abstract: Wind power has emerged as a vital renewable energy source. However, its inherent temporal variability and non-stationarity pose significant challenges for accurate forecasting. To solve this ...
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