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Global data center industry to emit 2.5 billion tons of CO2 through 2030, Morgan Stanley says
Global data center industry to emit 2.5 billion tons of CO2 through 2030, Morgan Stanley says
A boom in data centers is expected to produce about 2.5 billion metric tons of carbon dioxide-equivalent emissions globally through the end of the decade, and accelerate investments in decarbonization efforts, according to Morgan Stanley research.
Global data center industry to emit 2.5 billion tons of CO2 through 2030, Morgan Stanley says
Why have the big seven tech companies been hit by AI boom doubts?
Why have the big seven tech companies been hit by AI boom doubts?
Their shares have fallen 11.8% from last month’s peak but more AI breakthroughs may reassure investors
Dario Maisto, a senior analyst at Forrester, says a lack of economically beneficial uses for generative AI is hampering the investment case.“There is still an issue of translating this technology into real, tangible economic benefit,” he said.
Why have the big seven tech companies been hit by AI boom doubts?
GenAI sinks into the 'trough of disillusionment'
GenAI sinks into the 'trough of disillusionment'
GenAI faces growing skepticism as it struggles to deliver on high expectations Early excitement for ChatGPT and LLMs has shifted to concerns about costs, p | GenAI faces growing skepticism as initial excitement wanes, with the industry now focusing on overcoming practical and ethical challenges.
“People believe it really can solve a lot of things that it can't. I mean, the unfortunate thing is that OpenAI was amazing. But it was useless. It can't really do anything.”
GenAI sinks into the 'trough of disillusionment'
RT-2: New model translates vision and language into action
RT-2: New model translates vision and language into action
Introducing Robotic Transformer 2 (RT-2), a novel vision-language-action (VLA) model that learns from both web and robotics data, and translates this knowledge into generalised instructions for robotic control, while retaining web-scale capabilities. This work builds upon Robotic Transformer 1 (RT-1), a model trained on multi-task demonstrations which can learn combinations of tasks and objects seen in the robotic data. RT-2 shows improved generalisation capabilities and semantic and visual understanding, beyond the robotic data it was exposed to. This includes interpreting new commands and responding to user commands by performing rudimentary reasoning, such as reasoning about object categories or high-level descriptions.
RT-2: New model translates vision and language into action