Lifeboat Foundation

By Watching Unlabeled Videos.

Recent advances in machine learning (ML) and artificial intelligence (AI) are increasingly being adopted by people worldwide to make decisions in their daily lives. Many studies are now focusing on developing ML agents that can make acceptable predictions about the future over various timescales. This would help them anticipate changes in the world around them, including the actions of other agents, and plan their next steps. Making judgments require accurate future prediction necessitates both collecting important environmental transitions and responding to how changes develop over time.

Previous work in visual observation-based future prediction has been limited by the output format or a manually defined set of human activities. These are either overly detailed and difficult to forecast, or they are missing crucial information about the richness of the real world. Predicting “someone jumping” does not account for why they are jumping, what they are jumping onto, and so on. Previous models were also meant to make predictions at a fixed offset into the future, which is a limiting assumption because we rarely know when relevant future states would occur.

Continue reading “Google AI Proposes Multi-Modal Cycle Consistency (MMCC) Method Making Better Future Predictions” »

The new feature is part of Google’s Business Messages, a conversational messaging service that allows organizations to connect with people via Google Search, Google Maps, or their own business channels. For instance, Albertsons used Business Messages to share information with customers about vaccine administration. Suppose someone searched on Google for Safeway (an Albertson’s company). In that case, they could use the “message” button on Google Search to receive information like vaccine availability and how to book an appointment.

The new Bot-in-a-Box feature lets businesses launch a chatbot with an existing customer FAQ document, whether it’s from a web page or an internal document, to keep the service simple. The feature uses Google’s Dialogflow technology to create chatbots that can automatically understand and respond to customer questions without writing any code.

Showdown in a Kentucky Cavern: @WashingtonPost highlights DARPA’s latest Grand Challenge — #SubTChallenge — in Sunday (11÷14) magazine story Super Bowl of R… See more.

This three-year competition raises the question: How long until humans are obsolete?

SpaceX launches Crew-3, Tesla crashes, Elon Musk considers selling… again?

SpaceX launches Crew-3 and Starlink, Tesla’s Full Self-Driving potentially causes a crash, angered by Bernie Sanders, Elon Musk considers selling stock… again?

Dr. Ben Goertzel with Philip K. Dick at the Web Summit in Lisbon 2019.

Ben showcases the use of OpenCog within the SingularityNET enviroment which is powering the AI of the Philip K. Dick Robot.

Continue reading “Do Androids Dream of Electric Sheep? Dr. Ben Goertzel with Philip K. Dick at the Web Summit 2019” »

This month, the UW team upped their game.

Tapping into both AlphaFold and RoseTTAFold, they tweaked the programs to predict which proteins are likely to tag-team and sketched up the resulting complexes into a 3D models.

Using AI, the team predicted hundreds of complexes—many of which are entirely new—that regulate DNA repair, govern the cell’s digestive system, and perform other critical biological functions. These under-the-hood insights could impact the next generation of DNA editors and spur new treatments for neurodegenerative disorders or anti-aging therapies.

The year is almost at an end, and so it is once again time for the obligatory trends articles (Trends for 2022). We already know that AI is impacting every industry. In past articles I have covered “The tipping point”, the fact that AI is already immersed in our daily lives and with no end in sight. Here I outline seven areas where we can expect a greater involvement of AI in the lives of all of us, in 2022.

Data marketplaces.

AI thrives on data, and the rise and ubiquity of AI has placed a yet greater emphasis on the value of data as both a competitive advantage and a core asset to companies and countries alike. This in turn has risen to privacy laws and efforts to educate the public on how their data can be used. These efforts are geared towards giving individuals agency in exercising their data rights. The confluence of these factors is already leading to data marketplaces. Data marketplaces are online venues where individuals and corporations can buy and sell data. Data marketplaces have the potential to combine democratized access, privacy controls and monetization models to enable data owners to benefit from data use.

REE Automotive has revealed Leopard, its autonomous concept vehicle based on a brand new ultra-modular EV platform design. The full-scale concept is intended for customers, including last-mile autonomous and electric delivery companies, delivery fleet operators, e-retailers, and technology companies seeking to build fully autonomous solutions.

Developed with leading global delivery and technology companies focused on autonomous delivery and Mobility as a Service (MaaS) fleets, the Leopard concept vehicle measures 3.4 meters in length and just 1.4 meters in width. It is built on a home-brewed platform that contains the batteries, along with REEcorner units, front-wheel-steer, rear-wheel-drive, steering, suspension, motor, gearbox, and braking components.

Leopard is powered by a 50 kWh battery of unspecified range and an undisclosed type of electric motor that provides a top speed of 60 mph (96 km/h). It has a cargo capacity of 180 cubic feet (5 cubic meters) and a gross vehicle weight rating of 2 tonnes (2.2 tons). The vehicle is also designed to carry significantly more cargo due to REE’s low, flat floor.

A robot-assisted surgery was completed in Israel using the Da Vinci surgical system, by which the surgeon sits at a console and controls the robot.