While the work on DALL-E is amazing and will have a significant impact on the manufacture of memes, deep fakes, and other imagery that was once the domain of human artists (using prompts like " in the style of Edvard Munch's The Scream"), easy-to-use machine learning analytics involving the sorts of data that businesses and individuals create and work with every day can be just as disruptive (in the most neutral sense of that word). A growing class of "no-code" and "low-code" machine learning tools are making a number of ML tasks increasingly approachable, taking the powers of machine learning analytics that were once the sole provenance of data scientists and programmers and making them accessible to business analysts and other non-programming end users. "'Data-driven' is a reality for machine learning or data science projects!") But we learned a lot, and the biggest lesson was that machine learning succeeds only when you ask the right questions of the right data with the right tool. ("It turns out 'data-driven' is not just a joke or a buzzword," said Amazon Web Services Senior Product Manager Danny Smith when we checked in with him for some advice. Readers who have been with us for a while, or at least since the summer of 2021, will remember that time we tried to use machine learning to do some analysis-and didn't exactly succeed. Build a model from bad data and you get bad predictions and bad output-just ask the developers of Microsoft's Tay Twitterbot about that.įor a much less spectacular failure, just look to our back pages. What we call "AI" is dependent upon the construction of models from data using statistical approaches developed by flesh-and-blood humans, and it can fail just as spectacularly as it succeeds. (Spoiler alert: It has not.)Īnd as Ars' Matt Ford recently pointed out here, artificial intelligence may be artificial, but it's not "intelligence"-and it certainly isn't magic. And some people even think that an AI has attained sentience. Natural language processing (NLP) systems have grown closer to approximating human writing and text. Specialized algorithms, including OpenAI's DALL-E, have demonstrated the ability to generate images based on text prompts with increasing canniness. Over the past year, machine learning and artificial intelligence technology have made significant strides.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |