Amazon offers $29 skill builder courses; YC shrinks summer cohort; MIT advances ‘ analogue deep learning’

Y Combinator has cut the number of startups within its accelerator for the Summer 2022 batch by 40 percent, citing the global economic slowdown, TechCrunch reports. The cohort, currently on, has nearly 250 companies, while there were 414 companies in the previous batch, according to TechCrunch. AWS has launched new subscriptions to its cloud tech learning at attractive rates. And MIT researchers have built an artificial synapse that’s faster than those in the human brain. Notes: Y Combinator has cut the number of startups within its accelerator for the Summer 2022 batch by 40 percent, citing the global economic slowdown, TechCrunch reports. The cohort, currently on, has nearly 250 companies, while there were 414 companies in the previous batch, according to TechCrunch. This latest move by YC illustrates that even early-stage companies are not immune to the effects of the downturn, and in May, the accelerator advised founders to “plan for the worst,” TechCrunch notes. Amazon Web Services has launched Skill Builder Individual and Team subscriptions for as little as $29 in the US, a senior company executive announced in a blog post yesterday. “This is a new way for you to learn about cloud technologies and get practical experience with hands-on training,” Sebastien Stormacq, principal developer advocate at AWS, says in his post. The foundations are available online for free, and the new subscriptions announced yesterday give users access to a range of exclusive content to advance their cloud skills and prepare for AWS Certification exams with self-paced, digital training. The subscriptions allow users to learn AWS services with hands-on activities, according to Stormacq. Scientists and engineers in America’s Massachusetts Institute of Technology – or MIT as it’s known around the world – have developed a device that works like the synapses in the human brain, but a million times faster – which advances the field of analogue deep learning, the researchers said in a press release. Programmable resistors are the key building blocks in analog deep learning, just like transistors are the core elements for digital processors, they said. By repeating arrays of programmable resistors in complex layers, researchers can create a network of analogue artificial neurons and synapses that execute computations just like a digital neural network. This network can then be trained to achieve complex AI tasks like image recognition and natural language processing, according to the release. The MIT researchers set out to push the speed limits of a type of human-made analogue synapse that they had previously developed. They used a practical inorganic material in the fabrication process that enables their devices to run 1 million times faster than previous versions, which is also about 1 million times faster than the synapses in the human brain, they said in the release. This inorganic material also makes the resistor extremely energy efficient. Unlike materials used in the earlier version of their device, the new material is compatible with silicon fabrication techniques, according to the engineers. Theme music courtesy Free Music & Sounds: https://soundcloud.com/freemusicandsounds