Have you ever wondered about this concept called Mind reading? It might be a myth right. But a team of scientists led by neurosurgeon Edward Chang of University of California, San Francisco (UCSF) has developed an Artificial Intelligence (AI) that can converts someone's brain thoughts into text. Their study was published in Nature Neuroscience. In the study, in which four patients with epilepsy wore the implants to monitor seizures caused by their medical condition, the UCSF team ran a side experiment: having the participants read and repeat a number of set sentences aloud, while the electrodes recorded their brain activity during the exercise.
Scientists have developed an artificial intelligence system that can translate a person's thoughts into text by analysing their brain activity. Researchers at the University of California, San Francisco, developed the AI to decipher up to 250 words in real time from a set of between 30 and 50 sentences. The algorithm was trained using the neural signals of four women with electrodes implanted in their brains, which were already in place to monitor epileptic seizures. The volunteers repeatedly read sentences aloud while the researchers fed the brain data to the AI to unpick patterns that could be associated with individual words. The average word error rate across a repeated set was as low as 3 per cent.
Dr. Nicole Saphire explains the problem asymptomatic individuals present and why we're seeing so many deaths right now Get all the latest news on coronavirus and more delivered daily to your inbox. In a desperate plea for help, the commanding officer of the deployed aircraft carrier USS Theodore Roosevelt says his entire crew of roughly 5,000 sailors needs to be isolated after up to 200 onboard have tested positive for coronavirus. Three sailors on board the aircraft carrier tested positive last week, the first time the outbreak infected a deployed U.S. warship at sea. The letter from Captain Brett Crozier to top Navy brass was first obtained by the San Francisco Chronicle. Fox News exclusively reported Sunday there were 38 positive cases aboard the massive warship.
Engineer.ai, which uses Artificial Intelligence to help small and mid-sized organisations build their own bespoke software (custom or tailor-made software), has raised a Series A investment of $29.5 Mn, led by Lakestar and Jungle Ventures. The funding round also saw participation from DeepCore -- Softbank's AI-focussed investment fund. Founded by Sachin Dev Duggal and Saurabh Dhoot in 2012, Engineer.ai is a global company with split headquarters in Los Angeles and London, supported by offices in Delhi and Tokyo. The startup was formerly known as SD Squared and was rebranded to Engineer.ai. in June 2018. With over $24M in gross revenue and customers that include BBC, Virgin Group and the San Francisco Giants, Engineer.ai
Reading minds has just come a step closer to reality: scientists have developed artificial intelligence that can turn brain activity into text. While the system currently works on neural patterns detected while someone is speaking aloud, experts say it could eventually aid communication for patients who are unable to speak or type, such as those with locked in syndrome. "We are not there yet but we think this could be the basis of a speech prosthesis," said Dr Joseph Makin, co-author of the research from the University of California, San Francisco. Writing in the journal Nature Neuroscience, Makin and colleagues reveal how they developed their system by recruiting four participants who had electrode arrays implanted in their brain to monitor epileptic seizures. These participants were asked to read aloud from 50 set sentences multiple times, including "Tina Turner is a pop singer", and "Those thieves stole 30 jewels".
Fox News finds the coronavirus outbreak has left San Francisco streets and tourist sites including Chinatown and Fisherman's Wharf largely deserted. Get all the latest news on coronavirus and more delivered daily to your inbox. New drone footage and other video shot by Fox News shows once-busy streets and tourist areas in Los Angeles and San Francisco eerily deserted as the coronavirus has kept people indoors. Fisherman's Wharf, one of San Francisco's busiest tourist areas, once brimming with souvenir shops and seafood stalls and situated near Ghirardelli Square, was shuttered after the city's mayor called for a shelter-in-place, restricting people from leaving their homes except for trips to the grocery store or for medical supplies. The Golden Gate Bridge, which usually has seen over 100,000 cars and other vehicles a day and Alamo Square -- which overlooks the famous "Painted Ladies" -- were surprisingly barren.
An artificial intelligence can accurately translate thoughts into sentences, at least for a limited vocabulary of 250 words. The system may bring us a step closer to restoring speech to people who have lost the ability because of paralysis. Joseph Makin at the University of California, San Francisco, and his colleagues used deep learning algorithms to study the brain signals of four women as they spoke. The women, who all have epilepsy, already had electrodes attached to their brains to monitor seizures. Each woman was asked to read aloud from a set of sentences as the team measured brain activity.
Databricks's A.I. tool lets businesses turn raw data into actionable insights, according to the company. Computer hardware company HP used the tool to analyze customer data from 20 million devices and improve customer service by anticipating their future needs. Founded in 2013, the San Francisco-based startup has raised $900 million in funding from venture capital firms including Andreessen Horowitz. Microsoft is also a backer, following a successful partnership in 2017 to create Azure Databricks, an analytics platform for Microsoft customers.
A paper published by researchers at Carnegie Mellon University, San Francisco research firm OpenAI, Facebook AI Research, the University of California at Berkeley, and Shanghai Jiao Tong University describes a paradigm that scales up multi-agent reinforcement learning, where AI models learn by having agents interact within an environment such that the agent population increases in size over time. By maintaining sets of agents in each training stage and performing mix-and-match and fine-tuning steps over these sets, the coauthors say the paradigm -- Evolutionary Population Curriculum -- is able to promote agents with the best adaptability to the next stage. In computer science, evolutionary computation is the family of algorithms for global optimization inspired by biological evolution. Instead of following explicit mathematical gradients, these models generate variants, test them, and retain the top performers. They've shown promise in early work by OpenAI, Google, Uber, and others, but they're somewhat tough to prototype because there's a dearth of tools targeting evolutionary algorithms and natural evolution strategies (NES).
A preprint paper coauthored by Uber AI scientists and Jeff Clune, a research team leader at San Francisco startup OpenAI, describes Fiber, an AI development and distributed training platform for methods including reinforcement learning (which spurs AI agents to complete goals via rewards) and population-based learning. The team says that Fiber expands the accessibility of large-scale parallel computation without the need for specialized hardware or equipment, enabling non-experts to reap the benefits of genetic algorithms in which populations of agents evolve rather than individual members. Fiber -- which was developed to power large-scale parallel scientific computation projects like POET -- is available in open source as of this week, on Github. It supports Linux systems running Python 3.6 and up and Kubernetes running on public cloud environments like Google Cloud, and the research team says that it can scale to hundreds or even thousands of machines. As the researchers point out, increasing computation underlies many recent advances in machine learning, with more and more algorithms relying on distributed training for processing an enormous amount of data.