“We’ve been working on an experimental conversational AI service, powered by LaMDA, that we’re calling Bard. And today, we’re taking another step forward by opening it up to trusted testers ahead of making it more widely available to the public in the coming weeks.Bard seeks to combine the breadth of the world’s knowledge with the power, intelligence and creativity of our large language models. It draws on information from the web to provide fresh, high-quality responses. Bard can be an outlet for creativity, and a launchpad for curiosity, helping you to explain new discoveries from NASA’s James Webb Space Telescope to a 9-year-old, or learn more about the best strikers in football right now, and then get drills to build your skills.”
“The goal: to see if the tech can help our busy staff of reporters and editors with their job to cover topics from a 360-degree perspective. Will this AI engine efficiently assist them in using publicly available facts to create the most helpful content so our audience can make better decisions? Will this enable them to create even more deeply researched stories, analyses, features, testing and advice work we’re known for?
I use the term « AI assist » because while the AI engine compiled the story draft or gathered some of the information in the story, every article on CNET – and we publish thousands of new and updated stories each month – is reviewed, fact-checked and edited by an editor with topical expertise before we hit publish. That will remain true as our policy no matter what tools or tech we use to create those stories. And per CNET policy, if we find any errors after we publish, we will publicly correct the story.
Our reputation as a fact-based, unbiased source of news and advice is based on being transparent about how we work and the sources we rely on. So in the past 24 hours, we’ve changed the byline to CNET Money and moved our disclosure so you won’t need to hover over the byline to see it: « This story was assisted by an AI engine and reviewed, fact-checked and edited by our editorial staff. » We always note who edited the story so our audience understands which expert influenced, shaped and fact-checked the article.”
“In a project that could unlock the world’s research papers for easier computerized analysis, an American technologist has released online a gigantic index of the words and short phrases contained in more than 100 million journal articles — including many paywalled papers. The catalogue, which was released on 7 October and is free to use, holds tables of more than 355 billion words and sentence fragments listed next to the articles in which they appear. It is an effort to help scientists use software to glean insights from published work even if they have no legal access to the underlying papers, says its creator, Carl Malamud. He released the files under the auspices of Public Resource, a non-profit corporation in Sebastopol, California that he founded. ”
“These early results are encouraging, and we look forward to sharing more soon, but sensibleness and specificity aren’t the only qualities we’re looking for in models like LaMDA. We’re also exploring dimensions like “interestingness,” by assessing whether responses are insightful, unexpected or witty. Being Google, we also care a lot about factuality (that is, whether LaMDA sticks to facts, something language models often struggle with), and are investigating ways to ensure LaMDA’s responses aren’t just compelling but correct. But the most important question we ask ourselves when it comes to our technologies is whether they adhere to our AI Principles. Language might be one of humanity’s greatest tools, but like all tools it can be misused. Models trained on language can propagate that misuse — for instance, by internalizing biases, mirroring hateful speech, or replicating misleading information. And even when the language it’s trained on is carefully vetted, the model itself can still be put to ill use. ”
“Today, Amazon launched Alexa’s new Live Translation feature, which allows individuals speaking in two different languages to converse with each other, with Alexa acting as an interpreter and translating both sides of the conversation. With this new feature, a customer can ask Alexa to initiate a translation session for a pair of languages. Once the session has commenced, customers can speak phrases or sentences in either language. Alexa will automatically identify which language is being spoken and translate each side of the conversation. ”