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Tuesday, August 2, 2022

The Crypto Market Crashed. They’re Still Buying Bitcoin.

Hard-core Bitcoin evangelists are making the case that Bitcoin differs from the unstable crypto projects that sent the market into a tailspin.

Is Bio-Designed Collagen the Next Step in Animal Protein Replacement?

One company believes the possibilities go beyond vegan “meat,” from faux leather to luxury skin-care products. But is there enough demand outside of food alternatives?

Monday, August 1, 2022

A Cyberattack Illuminates the Shaky State of Student Privacy

At a moment when education technology firms are stockpiling sensitive information on millions of school children, safeguards for student data have broken down.

Navigating the Great Resignation and Changing Client Demands

With IP law firms under increasing pressure to meet client expectations faster and more efficiently, many practices are turning to creative workflow solutions and new staffing models. Register now for this free webinar.

Join us for the upcoming webinar, Driving IP Law firm growth amidst staffing and market challenges, as our in-house experts, with combined 40+ years of industry knowledge, share key learnings from the experiences of our IP law firm customers, including the considerations for getting it right and ensuring quality outcomes.

Topics that will be covered:

Finding a right-fit resourcing balance: when to outsource vs. keeping in-house
Common pitfalls to avoid
Key learnings and strategies for firms to manage resourcing successfully

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No code, no problem—we try to beat an AI at its own game with new tools

Over the past year, machine learning and artificial intelligence technology have made significant strides. Specialized algorithms, including OpenAI's DALL-E, have demonstrated the ability to generate images based on text prompts with increasing canniness. Natural language processing (NLP) systems have grown closer to approximating human writing and text. And some people even think that an AI has attained sentience. (Spoiler alert: It has not.)

And as Ars' Matt Ford recently pointed out here, artificial intelligence may be artificial, but it's not "intelligence"—and it certainly isn't magic. 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. 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.

For a much less spectacular failure, just look to our back pages. 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. ("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. "'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.

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After Pixar Ouster, John Lasseter Returns With Apple and ‘Luck’

John Lasseter was toppled five years ago by allegations about his workplace behavior. He’s back with an animated film and a studio that could be Pixar 2.0.

How Some Parents Changed Their Politics in the Pandemic

They were once Democrats and Republicans. But fears for their children in the pandemic transformed their thinking, turning them into single-issue voters for November’s midterms.