- Sundar Pichai at the company’s annual developer conference in Mountain View, experts are in short supply as companies in many industries rush to take advantage of recent strides in the power of artificial intelligence.
- At Google’s annual developer conference today, Pichai introduced a project called AutoML coming out of the company’s Google Brain artificial intelligence research group.
- The company is trying to lure new customers in the corporate cloud computing market, where it lags leader Amazon and second-place Microsoft (see “Google Reveals Powerful New AI Chip and is targeted at making it easier to use a technique called deep learning, which Google and others use to power speech and image recognition, translation, and robotics (see “10 Breakthrough Technologies 2013: Deep Learning”).
- “We do it by intuition,” says Quoc Le, a machine-learning researcher at Google working on the AutoML project.Last month, Le and fellow researcher Barret Zoph presented results from experiments in which they tasked a machine-learning system with figuring out the best architecture to use to have software learn to solve language and image-recognition tasks.On the image task, their system rivaled the best architectures designed by human experts.
- But like many ideas in the field of artificial intelligence, the power of deep learning is allowing new progress.
AI software that can help make AI software could accelerate progress on making computers smarter.
Continue reading “Why Google’s CEO Is Excited About Automating Artificial Intelligence”
- At the company’s annual developer conference in San Jose, California, this week, the company’s CEO Jensen Huang spoke to MIT Technology Review about how the machine-learning revolution is just starting.Nvidia has benefitted from a rapid explosion of investment in machine learning from tech companies.
- Software is eating the world, but AI is going to eat software.What industry will be transformed by machine learning next?
- Arterys recently got FDA approval for their cardiac imaging [which annotates scans of the heart], and I know of many others that are in the pipeline.Using machine learning in cars will also create new challenges for regulators.
- We probably have to break down some of these problems into smaller chunks.Your chips are already driving some cars: all Tesla vehicles now use Nvidia’s Drive PX 2 computer to power the Autopilot feature that automates highway driving.
- I’m not exactly sure, but we’ll find out.Intel, Google, and several other companies are now working on chips designed to accelerate machine learning (see “Battle to Provide Chips for the AI Boom Heats Up”).
Jensen Huang predicts that health care and autos are going to be transformed by artificial intelligence.
Continue reading “Nvidia CEO: Software Is Eating the World, but AI Is Going to Eat Software”
- Manipulating laser beams encoded with data offers a shortcut on certain tricky computing operations.
- Optalysys’s technology performs a mathematical function called the Fourier transform by encoding data, say a genome sequence, into a laser beam.
- French startup LightOn , founded earlier this year, has also built a system that uses optical tricks to process data being carried by laser light.
- As conventional chips don’t get faster any more, alternative routes look more attractive,” says Simon.
- “Computers really suck at this, [but] you can use nature to do it instead,” says Daudet.
The pace at which conventional chips improve is slowing, and these startups say optical computers are the answer.
Continue reading “Computing with Lasers Could Power Up Genomics and AI”