📺 In the first “Axios on HBO” special, Joe Biden accuses the media of misjudging how liberal the Democratic Party really is and dismisses the idea that Rep. Alexandria Ocasio-Cortez defines it.
This issue is 1,389 words, ~ a 5-minute read.
Illustration: Aïda Amer/Axios
AI is better at recognizing objects than the average human — but only under super-specific circumstances. Even a slightly unusual scene can cause it to fail, I report with Axios managing editor Alison Snyder.
Why it matters: Image recognition is at the heart of frontier AI products like autonomous cars, delivery drones and facial recognition. But these systems are held back by serious problems interpreting the messy real world.
Driving the news: Scientists from MIT and IBM will propose a new benchmark for image recognition next week at the premier academic conference on AI.
The goal is to put object recognition through more realistic paces.
The big picture: Ten years ago, image recognition got a huge boost from a humble source — a free database with millions of pictures of everyday things, paired with captions.
Key stat: Tested against the new MIT/IBM benchmark, ObjectNet, the performance of leading image-recognition systems dropped 40%–45%.
What's next: The creators of the new benchmark hope that more realistic tests will prod much-needed changes to AI.
Go deeper: Teaching robots to see — and understand
Illustration: Eniola Odetunde/Axios
A recently released AI program that generates hyper-realistic writing has become a powerful tool for storytelling, hinting at a new genre of computer-aided creativity.
What's happening: Inventive programmers are using it to generate poetry, interactive text adventures, and even irreverent new prompts for the popular game Cards Against Humanity.
The big picture: AI-written text is reaching new levels of realism — so much so that when scientists at OpenAI released a groundbreaking text generator earlier this year, they warned of potential dangers from mass-produced fake news. The risks are still present, but recent projects demonstrate the creative upsides.
How it works: The OpenAI language model is a bit like autocomplete: Based on an enormous amount of human writing, it predicts the best words to generate next. "Fine-tuning" it on a smaller corpus helps make it sound like an expert on that particular subject.
"It's good enough to generate a story that gets you emotionally invested," says Nick Walton, a senior at Brigham Young University and the creator of AI Dungeon 2. He says he spent somewhere between 200–500 hours on the side project — to the detriment of his GPA.
When they work, the game, the poetry and the cards can feel like magic. But in reality, they're using tricks of probability and dizzyingly enormous datasets to imitate human speech and all the thought that goes into it.
Go deeper: Where will predictive text take us? (The New Yorker)
Illustration: Sarah Grillo/Axios
Software features are rising to rival horsepower and styling for the most important elements of the driving experience, Axios transportation correspondent Joann Muller writes.
What's happening: Automakers face an urgent need to redesign their vehicles' electronic architecture to handle the onslaught of advanced features that will one day allow cars to talk to each other and drive themselves.
The big picture: With more than 100 million lines of code in the modern car, advanced software features are testing the limits of the computer hardware under the hood. And it will only get worse: Electric, connected and automated cars will devour even more computing power in the future
The software-driven shift will likely have massive implications for both the automotive and semiconductor industries.
The state of play: Today's cars typically have as many as 100 electronic control units (ECUs), each dedicated to a separate function — the engine, the window actuators or the lane-keeping system, for example.
What to watch: If the automobile evolves in the way cellphones, PCs and data centers did, there could be a lopsided contest to grab revenue, with a handful of winners and many losers, warns KPMG in a new report.
Illustration: Rebecca Zisser/Axios
Tech's liability shield becomes trade-deal flashpoint (Margaret Harding McGill - Axios)
China's overblown AI investments (Karen Hao - MIT Tech Review)
2020 Democrats answer 7 key tech questions (Emily Stewart & Rani Molla - Vox)
Taking virtual reality for a test drive (Patricia Marx - The New Yorker)
An e-waste sting ends in betrayal (Colin Lecher - The Verge)
Multilingual brochures. Photo: Jeffrey Greenberg/Universal Images Group/Getty
A new map from the Endangered Language Alliance plots more than 600 languages onto a map of New York City, placing them near sites where they're spoken.
The result is an incredibly dense, colorful spread that spans the city's usual suspects — Puerto Rican Spanish, Cantonese, Russian — plus tons of infrequently heard languages, like Syriac, Balti and Jola.
Go deeper: Lost languages found in New York (NYT)