This week’s great tech stories from around the web (until April 9th)


OpenAI’s DALL-E 2 produces fantastic images of almost anything you can imagine
Andrew Tarantola | Engadget
“DALL-E 2, which uses OpenAI’s CLIP image recognition system, builds on these image generation capabilities. Users can now select and edit specific areas of existing images, add or remove elements along with their shadows, merge two images into a single collage, and create variations of an existing image. Additionally, the output images are 1024 pixel squares, compared to the 256 pixel avatars the original version generated. OpenAI’s CLIP is designed to look at a specific image and summarize its content in a way that humans can understand. The consortium reversed this process and built a picture from their summary as they worked with the new system.”


NASA sets a new date for the first launchpad test of its mega lunar rocket
Trevor Mogg | digital trends
“If everything goes according to plan and no further technical problems arise, hopefully NASA will be able to prepare for the first launch of the SLS rocket and the Orion spacecraft in the next few months. The unmanned Artemis I mission will send Orion on a moon flyby in a comprehensive test of its space systems. Artemis II will fly the same route but with a crew on board, while the highly anticipated Artemis III mission, currently scheduled no earlier than 2024, will land the first woman and first person of color on the lunar surface.”.”


As Russia plans its next move, an AI listens to the chatter
Becomes a Knight | Wired
“As the soldiers spoke, an AI listened. Her words were automatically captured, transcribed, translated and analyzed using multiple artificial intelligence algorithms developed by Primer, a US company providing AI services to intelligence analysts. Although it is not clear whether Ukrainian troops also intercepted communications, the large-scale use of AI systems to monitor the Russian army shows the growing importance of sophisticated open-source intelligence in military conflicts. A number of unsecured Russian broadcasts were posted online, translated and analyzed on social media. Other data sources, including smartphone video clips and social media posts, were also scrutinized. But it is the use of natural language processing technology to analyze Russian military communications that is particularly novel.”


Elon Musk is on the board of directors of Twitter. What could go wrong?
Chris Stokel-Walker | Wired
“Musk’s hot-and-cold relationship with Twitter sheds little light on why he bought into the company and joined its board, although theories abound. Musk did not respond to a request for comment. A clue was found in his recent Twitter posts. The entrepreneur has long been an open book on the social network, saying in 2018, “My tweets are literally what I’m thinking right now, not carefully crafted corporate Bs, which is really just mundane propaganda.” And recent tweets relate to the future direction of the platform. Since buying his stake in the company, Musk has questioned his followers about whether Twitter should open source its algorithm for verification and whether the platform adheres to the principle of free speech.”


The latest skill of this Japanese robot: peeling a banana
University of Tokyo via Reuters | NBC News
“While the two-armed machine only succeeds 57 percent of the time, banana peeling hints at a future where machines will perform more subtle operations than moving metal parts or delivering coffee. A video by researchers from the University of Tokyo showed the robot picking up and peeling a banana with both hands in about three minutes. Researchers Heecheol Kim, Yoshiyuki Ohmura, and Yasuo Kuniyoshi trained the robot using a “deep imitation learning” process, in which they demonstrated the action of peeling bananas hundreds of times to produce enough data for the robot to learn and mimic the actions. “


Nvidia’s next GPU shows Transformers transforming AI
Samuel K Moore | IEEE spectrum
“The secret of the Transformer engine is its ability to dynamically select the level of accuracy required for each layer in the neural network at each step in training a neural network. The least precise units, the 8-bit floating point, can speed up their calculations, but then produce 16-bit or 32-bit sums for the next layer if that’s the precision needed there. However, Hopper goes one step further. The 8-bit floating point units can perform their matrix calculations on either of two forms of 8-bit numbers.”


Tesla officially opens Texas Gigafactory
Will Douglas Sky | MIT Technology Review
“It is the company’s fourth plant in the United States, following the vehicle plant in Fremont, California, the battery plant in Sparks, Nevada and the solar plant in Buffalo, New York. Tesla also has a vehicle factory outside of Shanghai, China and recently opened its first European factory near Berlin, Germany. Tesla spent an estimated $5 million to purchase the property outside of Austin, plus another $1.1 billion to build the plant. “We need a place where we can be really big, and there’s no place like Texas,” Musk said. ‘We’re going to be moving on a really massive scale.’”

Photo credit: tunnelmotions / 71 images

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