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OpenAI says Voice Engine might be too risky to release

OpenAI says it ran a small-scale test of its new voice cloning product Voice Engine with a few select partners. The results show promising applications for the tech, but safety concerns may keep it from being released. OpenAI says that Voice Engine can clone a human’s voice based on a single 15-second recording of their voice. The tool can then generate “natural-sounding speech that closely resembles the original speaker.” Once cloned, Voice Engine can turn text inputs into audible speech using “emotive and realistic voices.” The tool’s capability makes exciting applications possible but raises serious safety issues too. Promising use

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Amazon takes $2.75 billion plunge into Anthropic

Amazon announced a colossal $2.75 billion investment in AI startup Anthropic. Anthropic’s Claude 3 Opus is officially the most powerful LLM on the planet, marginally usurping heavyweight GPT-4 on the LMSys leaderboard. Anthropic has received billions in funding from numerous sources, including Amazon and Google, becoming the chief rival to  OpenAI.   Amazon is now shoveling coal in Anthropic with a new influx of funds, adding to the company’s previous $1.25 billion investment. This brings its total commitment to a staggering $4 billion. This deal, valued based on Anthropic’s last $18.4 billion valuation, is one of the biggest bets of the

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Top Sustainability and Renewable Energy Courses (2024)

In today’s rapidly changing world, where environmental sustainability and energy conservation have become pivotal, acquiring knowledge in sustainability and renewable energy is not just beneficial but essential. These fields embody critical skills that cater to the urgent need for a sustainable future, addressing global challenges such as climate change, resource depletion, and environmental degradation. As […]

Which AI-Leading Countries Are Most Interested In Deep-Fake Creation?

While the proliferation of AI tools and technology has already delivered numerous benefits to individuals and businesses alike, it’s also true that the increased accessibility to AI tools has had harmful consequences on the level of misinformation put out into the world. The use of deep fakes to misrepresent influential figures is a growing concern…

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Bringing the end-user into the AI picture!

There is a ton of information these days on every single phase involved in building AI algorithms, and this is great!  This covers loading/preparing data, feature engineering, training, testing, hyper-parameterization, validation, explainability, MLOps, and deployment.  Overlooking End-Users in AI Applications At the same time, I am puzzled to see how little is mentioned about the […]

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