Small and energy-efficient models have garnered growing attention in recent months.
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While this is a recognized problem in face-reading AI models, Nvidia’s tech relies on synthetic data to achieve balance, which comes with caveats.
After a slump through the latter half of the last decade, the US is experiencing a startup tsunami, according to The Economist.
Microsoft wants its language models to be a little more adaptable.
Microsoft hasn’t signed off on OpenAI’s dramatic reversal of its onetime plan to become a for-profit venture.
A recent IBM patent shows that it may be working on Grammarly for software developers.
JPMorgan Chase is tackling human biases with two recent patents.
Disney wants to use AI to help you recall fond memories.
Quarterly earnings at tech giants Meta and Microsoft surged, indicating that multi-billion dollar AI investments are starting to pay off.
However, these kinds of modifications come at the expense of high-level customization and accuracy.
Does the AI hype actually hold any substance? As long as you don’t get distracted by shiny things, these venture capitalists say.
he filing adds to several patents from tech companies that aim to tackle the deepfake problem amid the proliferation of generative AI.
IBM is booting up its domestic production, setting aside $150 billion to make computers in the US over the next five years.
Along with mitigating hallucinations, this tech creates an audit trail for more transparency between the model and its users.
One point Chinese AI companies including Tencent and DeepSeek emphasize about their new models: efficiency.
This new server farm announcement comes just after Apple CEO Tim Cook reportedly paid President Trump a visit.