Gen AI can save you time, but once you’re using it frequently, the process of repeatedly uploading the same background files and re-entering prompts for common tasks can really eat into your efficiency gains.
Artificial intelligence is everywhere. And the recent explosion of new AI technologies and tools has introduced many new terms that you need to know to understand it.
The technology fuels virtual assistants, like Apple’s Siri, helps physicians to spot cancer in MRIs and allows your phone to recognize your face.
The relentless hype surrounding generative AI in the past few months has been accompanied by equally loud anguish over the supposed perils — just look at the open letter calling for a pause in AI experiments. This tumult risks blinding us to more immediate risks — think sustainability and bias — and clouds our ability to appreciate the real value of these systems: not as generalist chatbots, but instead as a class of tools that can be applied to niche domains and offer novel ways of finding and exploring highly specific information.
Mind reading is common among us humans. Not in the ways that psychics claim to do it, by gaining access to the warm streams of consciousness that fill every individual’s experience, or in the ways that mentalists claim to do it, by pulling a thought out of your head at will. Everyday mind reading is more subtle: We take in people’s faces and movements, listen to their words and then decide or intuit what might be going on in their heads.
Artificial intelligence has become the tech industry’s shiny new toy, with expectations it’ll revolutionize trillion-dollar industries from retail to medicine. But the creation of every new chatbot and image generator requires a lot of electricity, which means the technology may be responsible for a massive and growing amount of planet-warming carbon emissions.
Whereas there’s an enormous quantity of knowledge obtainable for HR and expertise analytics in the present day, most organizations are nonetheless not reaping the advantages of their analytics investments. Gartner reports that solely 21% of HR leaders agree that their organizations are successfully utilizing expertise information to form expertise acquisition and recruiting methods, enhance worker engagement and inform different enterprise selections.
DeepMind, the AI research laboratory funded by Google’s parent company, Alphabet, today published the results of a collaboration between it and mathematicians to apply AI toward discovering new insights in areas of mathematics. DeepMind claims that its AI technology helped to uncover a new formula for a previously-unsolved conjecture, as well as a connection between different areas of mathematics elucidated by studying the structure of knots.
A team of researchers from the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) announced last Wednesday (21) the creation of a decryption algorithm capable of automatically providing the meaning of languages long lost, even if not have any relation to other languages.
This week at the 2020 International Society for Music Information Retrieval Conference, Spotify open-sourced Klio, an ecosystem that allows data scientists to process audio files (or any binary files) easily and at scale. It was built to run Spotify’s large-scale audio intelligence systems and is leveraged by the company’s engineers and audio scientists to help develop and deploy next-generation audio algorithms.
