
More of AI, Less of People: GitHub Fires India Engineering Team
The statements seem like an oblique admission that Microsoft wants to save money spent on employees and invest it in the AI race that is getting hotter by the minute
The statements seem like an oblique admission that Microsoft wants to save money spent on employees and invest it in the AI race that is getting hotter by the minute
Unlike calculators, the petition circulation does not exist at the policy level, but at the research level
The Google-DeepMind partnership would be a befitting reply to Microsoft-OpenAI alliance
While OpenAI apparently utilised 10,000 NVIDIA GPUs to train ChatGPT, Cerebras claims to have trained their models to the highest accuracy for a given compute budget.
With the Google partnership, Replit believes that they will now get access to newer models as they are released which will ultimately reach the developers and help with the goal of “accelerating tech into everyone’s hands”
AI regulation might have a crypto-SEC moment soon.
Today, retail technology is developing at a fast pace – whether it is business transformation or even exploring emerging tech (AR/VR and metaverse etc.) to give customers a more experiential journey. Businesses are innovating not only to remain relevant, but also, ahead. Some are really shaping the future of omni-channel retail by predicting customer expectations and market trends.
Chip companies may be ‘moonlighting’ to China, the market that’s down but not out, as they continue to make beeline to invest in the country
When it comes to the current capabilities of LLMs and generative AI, Apple has been surprisingly quiet.
OpenAI, the startup that captured the world’s attention with ChatGPT, is once again setting its sights on developing robots. The San Francisco-based startup recently invested
AMD and NVIDIA go head to head on image upscaling technologies. But who will win?
Data-centric AI is an emerging approach that places data at the forefront of AI development. Rather than focusing only on developing sophisticated models or endlessly refining such models, data-centric AI emphasises the importance of quality data in training the models effectively. This approach can be particularly useful in the field of unstructured document processing, where ensuring the quality of training data could be a huge challenge.
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