Google DeepMind has unveiled new research on AI tech it calls V2A (“video-to-audio”) that can generate soundtracks for videos. The initiative complements the wave of AI video generators from companies ranging from biggies like OpenAI and Alibaba to startups such as Luma and Runway, all of which require a separate app to add sound. V2A technology “makes synchronized audiovisual generation possible” by combining video pixels with natural language text prompts “to generate rich soundscapes for the on-screen action,” DeepMind writes, explaining that it can “create shots with a dramatic score, realistic sound effects or dialogue.” Continue reading DeepMind’s V2A Generates Music, Sound Effects, Dialogue

Google is implementing an internal reorganization that combines its Android and hardware teams. Google CEO Sundar Pichai announced a new Platforms & Devices team headed by Rick Osterloh, which includes Android, Chrome, ChromeOS, Photos and all Pixel products. Pichai says the move will help speed development. Osterloh’s mandate is full-stack platform development that smoothly incorporates AI across all Google platforms, including smartphones, TVs and anything with Android OS. Hiroshi Lockheimer, who previously ran ops for Android, Chrome and ChromeOS, moves on to other projects at Google and Alphabet. Continue reading Google Merges Android and Hardware Units for AI Efficiency

Sam Altman continues to call for coordinated international regulation of artificial intelligence. The OpenAI co-founder and CEO visited Seoul this past weekend to meet with South Korean President Yoon Suk Yeol, who issued a statement saying it is important to act “with a sense of speed” in establishing international standards or face unwanted “side effects.” Altman also virtually delivered a keynote address to Chinese AI researchers at an annual conference hosted by the Beijing Academy of Artificial Intelligence, calling on China to participate in global rulemaking. Continue reading Altman Calls on China to Participate in Global AI Rulemaking

In a move it sees as a force multiplier, Alphabet is consolidating DeepMind and the Brain team from Google Research into a unit called Google DeepMind, uniting the teams responsible for Google Brain with DeepMind, the UK-based artificial intelligence research lab acquired in 2014. Collective accomplishments include AlphaGo, Transformers, WaveNet and AlphaFold, as well as software frameworks like TensorFlow and JAX for expressing, training and deploying large scale ML models. “Combining all this talent into one focused team, backed by the computational resources of Google, will significantly accelerate our progress in AI,” the company announced. Continue reading Google Restructures AI Research Units into Google DeepMind

Respected members of the advanced tech community are going on record opposing the faction calling for a “pause” in large-model artificial intelligence development. Meta Platforms chief AI scientist Yann LeCun and DeepLearning.AI founder and CEO Andrew Ng, formerly at Alphabet where he helped launch Google Brain, were joined this past week by Bill Gates and former Google CEO Eric Schmidt in opposing the proposed six-month halt to development of AI models more advanced than OpenAI’s GPT-4, which is said to train on a trillion parameters — more than 500 times that of GPT-3. Continue reading Mixed Reactions to ‘Pause’ on AI Models Larger than GPT-4

Stability AI is in the first stage of release of Stable Diffusion, a text-to-image generator similar in functionality to OpenAI’s DALL-E 2, with one important distinction: this open-source newcomer lacks the filters that prevent the earlier system from creating images of public figures or content deemed excessively toxic. Last week the Stable Diffusion code was made available to just over a thousand researchers and the Los Altos-based startup anticipates a public release in the coming weeks. The unfettered unleashing of a powerful imaging system has stirred controversy in the AI community, raising ethical questions. Continue reading Stability AI Releases Stable Diffusion Text-to-Image Generator

Google and Ascension, the second-largest health system in the U.S., have been collecting the personal health data of tens of millions of people in 21 states. Project Nightingale, the tech giant’s effort to enter healthcare, has culled lab results, diagnoses and hospitalization records, which include patient names and dates of birth. No doctor or patient has been notified, which has sparked a federal inquiry, but some experts say the initiative is permissible since Google is developing software to improve the healthcare system. Google explained that its partnership with Ascension is not a secret and was first announced in July during a Q2 earnings call. Continue reading Google Culls Patient Data to Build Healthcare Search Tools

Google research scientists report that they have produced realistic frames from open source video data sets at scale. Neural networks are able to generate complete videos from only a start and end frame, but it’s the complexity, information density and randomness of video that have made it too challenging to create such realistic clips at scale. The scientists wrote that, to their knowledge, “this is the first promising application of video-generation models to videos of this complexity.” The systems are based on a neural architecture known as Transformers, as described in a Google Brain paper, and are autoregressive, “meaning they generate videos pixel by pixel.” Continue reading Google Scientists Generate Realistic Videos at Scale with AI

In his CES pre-show keynote presentation, LG Electronics president and chief technology officer Dr. I.P. Park set the stage for an AI-infused vision of tomorrow by questioning if we are “making our lives better, how much better, and better how?” Park called on XPRIZE Foundation founder and executive chairman Peter Diamandis to illustrate what artificial intelligence enables and Landing AI founder and CEO Andrew Ng to explain how AI technologies will evolve. Open-source webOS and 5G were the cornerstone technologies for the product demonstrations by Luxoft and Qualcomm, respectively. Continue reading CES Keynote: LG Exec Asks if Life Is Better and By How Much

According to members of Google’s Brain and Machine Perception teams, researchers at the tech giant have developed “ways to make machine-generated speech sound more natural to humans,” even providing examples of the more expressive speech in a company blog post, reports VentureBeat. Google also announced the release of its Cloud Text-to-Speech services, which could “be used to bring more natural speech to devices, apps or digital services that utilize voice control or voice computing,” the article explains.

Continue reading Google’s Machine-Generated Speech Will Sound More Human

The latest project out of Google Brain, the company’s machine learning research lab, has been using AI software to write Wikipedia-style articles by summarizing information on the Internet. But it’s not easy to condense social media, blogs, articles, memes and other digital information into salient articles, and the project’s results have been mixed. The team, in a paper just accepted at the International Conference on Learning Representations (ICLR), describes how difficult it has been. Continue reading Google Brain Leverages AI to Generate Wikipedia-Like Articles

In May, research project Google Brain debuted its AutoML artificial intelligence system that can generate its own AIs. Now, Google has unveiled an AutoML project to automate the design of machine learning models using so-called reinforcement learning. In this system, AutoML is a controller neural network that develops a “child” AI network for a specific task. The near-term goal is that AutoML would be able to create a child that outperforms human versions. Down the line, AutoML could improve vision for autonomous vehicles and AI robots. Continue reading Google Intends to Advance Machine Learning With its AutoML

Google Senior Fellow Jeff Dean, who works on the Google Brain team, recently highlighted AutoML (for machine learning), a project aimed at using AI-empowered machines to build other AI machines, removing humans from the equation. The need for AI algorithms grows as its capabilities are becoming important to a wide range of industries. But only an estimated 10,000 people worldwide have the education, expertise and ability to construct those algorithms, and Facebook, Google and Microsoft pay millions of dollars for them. Continue reading Google Project Aims to Use AI to Develop More AI Algorithms

Amazon is developing systems based on artificial intelligence algorithms that are aimed at spotting fashion trends and, eventually, shaping them. The effort could boost Amazon’s sales in clothing, perhaps even gaining a dominant position in fashion. The e-commerce giant isn’t alone in making recommendations based on products appearing in social media, and highlighting the resulting trends; Instagram and Pinterest also pinpoint trends and react quickly to them, as does startup subscription service Stitch Fix. Continue reading Amazon Creates AI-Based Tools for Spotting Fashion Trends

The new Microsoft Research AI lab is now open for business, targeting the creation of a single system of general artificial intelligence that can flexibly work on a range of problems. Based at company headquarters in Washington state, the lab will be home to more than 100 scientists whose AI research spans fields including perception, learning, reasoning and natural language processing. The lab’s goal of general AI differs from narrow AI, which performs one task very well, such as facial recognition. Continue reading Microsoft Takes a Bigger Stake in AI With New Lab, Projects