Lifeboat Foundation

From A to B, check out this week’s awesome tech stories from around the web.

Top 10 upcoming future technologies | trending technologies | 10 upcoming tech.

Future technologies are currently developing at an acclerated rate. Future technology ideas are being converted into real life at a very fast pace.

Continue reading “10 Upcoming Future Technologies: How They’ll Impact Your Life” »

SUMMARY Researchers at the George Washington University, together with researchers at the University of California, Los Angeles, and the deep-tech venture startup Optelligence LLC, have developed an optical convolutional neural network accelerator capable of processing large amounts of information, on the order of petabytes, per second. This innovation, which harnesses the massive parallelism of light, heralds a new era of optical signal processing for machine learning with numerous applications, including in self-driving cars, 5G networks, data-centers, biomedical diagnostics, data-security and more.

THE SITUATION Global demand for machine learning hardware is dramatically outpacing current computing power supplies. State-of-the-art electronic hardware, such as graphics processing units and tensor processing unit accelerators, help mitigate this, but are intrinsically challenged by serial data processing that requires iterative data processing and encounters delays from wiring and circuit constraints. Optical alternatives to electronic hardware could help speed up machine learning processes by simplifying the way information is processed in a non-iterative way. However, photonic-based machine learning is typically limited by the number of components that can be placed on photonic integrated circuits, limiting the interconnectivity, while free-space spatial-light-modulators are restricted to slow programming speeds.

THE SOLUTION To achieve a breakthrough in this optical machine learning system, the researchers replaced spatial light modulators with digital mirror-based technology, thus developing a system over 100 times faster. The non-iterative timing of this processor, in combination with rapid programmability and massive parallelization, enables this optical machine learning system to outperform even the top-of-the-line graphics processing units by over one order of magnitude, with room for further optimization beyond the initial prototype.

After six years of peace, the two tech giants are on course to butt heads again over the future of artificial intelligence.

Microsoft is about to go head-to-head with Google in a battle for the future of search. At a press event later today, Microsoft is widely expected to detail plans to bring OpenAI’s ChatGPT chatbot to its Bing search engine. Google has already tried to preempt the news, making a rushed announcement yesterday to introduce Bard, its rival to ChatGPT, and promising more details on its AI future in a press event on Wednesday.

The announcements put the two tech behemoths, known for their previous skirmishes with each other, on a collision course as they compete to define the next generation of search.

Continue reading “Microsoft will let companies create their own custom versions of ChatGPT, source says” »

Amazon is engaging with Times Internet to explore the acquisition of MX Player, one of the largest on-demand video streaming services in India, according to four sources familiar with the matter, as the American e-commerce group eyes expanding its entertainment ambitions in the key overseas market.

The deliberations are ongoing and may not materialize into a deal, three sources cautioned. The terms of the deal are yet to be finalized. Times Internet and Amazon did not immediately respond to a request for comment. Sources requested anonymity discussing private matters.

At least two more players — including Zee-Sony — have expressed interest in acquiring the Times Internet-owned app, two sources said.

A team of researchers have come up with a machine learning-assisted way to detect the position of shapes including the poses of humans to an astonishing degree — using only WiFi signals.

In a yet-to-be-peer-reviewed paper, first spotted by Vice, researchers at Carnegie Mellon University came up with a deep learning method of mapping the position of multiple human subjects by analyzing the phase and amplitude of WiFi signals, and processing them using computer vision algorithms.

“The results of the study reveal that our model can estimate the dense pose of multiple subjects, with comparable performance to image-based approaches, by utilizing WiFi signals as the only input,” the team concluded in their paper.

Game on!

Google PR:

Continue reading “Google to launch ChatGPT Competitor, Bard, Conversational AI, LaMDA based” »

In my chat with Serene, an internet freedom activist and former Google Ideas engineer, I ask: “Am I allowed to speak with you right now? Legally?”“We’re both in the U.S., so yes, I think we’re good,” she answers.

As one of the few tools for accessing blocked and censored information on the web, Serene’s Snowflake is widely used by citizens of oppressive regimes. It is primarily done using Tor, an open-source browser that enables secure, private, and anonymous internet browsing.

She is now unveiling Snowstorm, an upgraded version of Snowflake, which Serene claims will be faster, more generalized, and have more features. Snowstorm is fast enough to stream YouTube videos, something previous versions could not do.

Continue reading “As The Internet Freedom Project Expands, Snowflake Becomes Snowstorm” »

Today’s Internet is in the early stages of being transformed once again—this time, instead of search, social, mobile, etc.—it’s going to be a Web that supports conversations.