Scale AI hits $3.5B valuation as it turns the AI boom into a venture bonanza
Kirsten KorosecTue, December 1, 2020, 1:35 PM PST·3 min read
Scale AI, the four-year-old data labeling startup, has discovered that selling the picks and shovels needed to develop and apply artificial intelligence is big business.
The company, which created a visual data labeling platform that uses software and people to label image, text, voice and video data for companies building machine learning algorithms, has raised another $155 million. The funding round, led by Tiger Global, pushes Scale's post-money valuation to more than $3.5 billion.
Importantly, Scale is now a "break even" business and is set up to continue to add employees and expand into new markets in a sustainable way, Scale's CEO and co-founder Alexandr Wang told TechCrunch. Scale will use the funds to grow its workforce from 200 people to about 350 by the end of next year. (Those employee numbers don't include the tens of thousands of contractors it uses to label data.) It's also focused on new markets and adding products and platform capabilities.
Scale got its start by supplying autonomous vehicle companies with the labeled data needed to train machine learning models to develop and deploy robotaxis, self-driving trucks and automated bots used in warehouses and on-demand delivery. Legacy automakers such as General Motors and Toyota, chipmaker Nvidia and a slew of AV startups, including Nuro and Zoox, have used its platform.
More recently, Scale's customers have spilled over into government, e-commerce, enterprise automation and robotics. Airbnb, OpenAI, DoorDash and Pinterest are some of its customers. That pace of expansion has accelerated in 2020, according to Wang.
See the full story here: https://www.yahoo.com/entertainment/scale-ai-hits-3-5b-213539913.html
Understanding the AI factory
In Competing in the Age of AI, the authors introduce the concept of the “data pipeline,” a set of components and processes that consolidate data from various internal and external sources, clean the data, integrate it, processes it, and store it for use in different AI systems. What’s important, however, is that the data pipeline works in a “systematic, sustainable, and scalable way.” This means that there should be the least amount of manual effort involved to avoid causing a bottleneck in the AI factory.
Iansiti and Lakhani also expand on the challenges involved in the other aspects of the AI factory, such as establishing the right metrics and features for supervised machine learning algorithms, finding the right split between human expert insight and AI predictions, and tackling the challenges of running experiments and validating the results.
See the full story here: https://bdtechtalks.com/2020/12/02/competing-in-the-age-of-ai/
New artwork uses artificial intelligence and gaming tech to create worlds
You could stand immersed forever in a new artwork at the Christchurch Art Gallery and never see the same thing twice.
In just one brief glimpse, three large projectors show a computer-generated giant egg with legs running precariously across a surreal and colourful virtual landscape. Then a figure with a polka dot face and a 1980s video projector with a head enter the scene and collide with the egg.
In Kahoots, a collaboration between artists Sean Kerr and Judy Darragh, is a humorous, surreal and surprising artwork that uses video game technology to immerse viewers in a self-generated virtual world.
Kerr used the artificial intelligence and machine learning functions of software designed to make video games to create a work that seems to have a mind of its own.
Live feeds from the virtual world are projected on three large walls in an exhibition space at the Christchurch Art Gallery. A fourth wall is covered in reflective foil and LED signs in the middle of the room feature animated flames.
See the full story here: https://www.stuff.co.nz/entertainment/arts/123516534/new-artwork-uses-artificial-intelligence-and-gaming-tech-to-create-worlds
Opteran Technologies receives $2.8M to develop an AI honeybee brain
Opteran Technologies, has just raised $2.8 million to build AI systems modeled on honeybee brains.
Marshall told Digital Trends, “If you’re going to start building a model of any brain on the planet, why on Earth would you start with the most complicated one?”
Thinking Small
In the tech world, big ideas are usually what earn the biggest payday. However, it’s clear that thinking on a large scale is slowing down the process of AI development. Marshall and his team believe that focusing on smaller, more attainable goals is the key to eventual large-scale success.
That isn’t just a hypothesis. Data has already proven that honeybees are good problem solvers. Researchers from the University of London found that bees solved the traveling salesman problem faster than the world’s top supercomputers. The test requires the bee or computer to find the shortest route between flowers that are discovered in a random order.
See the full story here: https://www.theburnin.com/startups/opteran-technologies-ai-honeybee-brain-2020-11-28/
How to Turn Your TV Into a Remote Meeting Paradise
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https://onezero.medium.com/how-to-turn-your-tv-into-a-remote-meeting-paradise-3a0a8bedbd48
Can virtual reality offices recreate a coworker culture at home?
"You have the sense that you're in a real meeting, so if you're using those VR networking platforms, then you can meet as avatars with your other coworkers. You could also collaborate on design," says David Ripert, chapter president of the UK branch of the global VR/AR Association.
He describes VR as the "silver lining" of the pandemic, as companies are using it more and more to recreate physical events and conferences.
See the full story here: https://newseu.cgtn.com/news/2020-11-27/Can-virtual-reality-offices-recreate-a-coworker-culture-at-home--VINvQT1P5m/index.html