Google is readying an API and other enterprise tools for its Pathways Language Model (PaLM) — a large language model similar to GPT — to encourage developers to create chatbots and other apps using the platform. PaLM is one of Google’s most advanced systems, with the capability to generate text, images, code, video and audio from natural language prompts. Much like OpenAI’s GTP series and the LLaMA family from Meta Platforms, it is suitable for a wide variety of general tasks. To facilitate PaLM’s use for specific tasks, Google is launching the MakerSuite along with the PaLM API. Continue reading Google’s PaLM API, MakerSuite Coming to Select Developers

Meta Platforms has unveiled a new generative artificial intelligence language system called LLaMA, which doesn’t chat, but is designed as a research tool the company hopes will help “democratizing access in this important, fast-changing field.” The LLaMA (Large Language Model Meta AI) ranges in size from 7B to 65B parameters. Touted as a “smaller, more performant model,” LLaMA enables those members of the research community that do not “have access to large amounts of infrastructure to study these models,” Meta explains. Training smaller foundation models requires less computing power and resources for testing and validation. Continue reading Meta Says Its LLaMA AI for Researchers Does More with Less

Alphabet is touting artificial intelligence advances as it faces disappointing Q4 earnings, with CEO Sundar Pichai, who is also CEO of Google, telling analysts the company will soon share its own generative AI system with the public, competing head-on with OpenAI’s ChatGPT and DALL-E. “In the coming weeks and months, we’ll make these language models available, starting with LaMDA, so that people can engage directly with them,” Pichai said. Google’s parent company reported a 3.6 percent decline in core ad revenue, at $59 billion in Q4, while overall revenue was up 1 percent to $76 billion. Continue reading Alphabet Reveals Major AI Push, Plans to Take On ChatGPT

Google seems to view ChatGPT as a threat to its $149 billion annual search business. OpenAI’s chatbot is said to have amazed those who’ve seen its ability to grasp concepts and generate ideas, which Google execs are concerned might translate to “a compelling new search experience,” according to reporting by The New York Times. Sundar Pichai, CEO of Alphabet and Google, is said to have wrangled Google founders Larry Page and Sergey Brin for “several meetings” focused on ratcheting up Google’s AI development in an effort to overtake ChatGPT’s first-mover advantage. Continue reading Google Taps Page and Brin to Take on ChatGPT for AI Search

DeepMind researchers have trained an AI to solve computer coding challenges as well as the average person. In a paper published last week in the journal Science, the group from Google’s AI division described how AlphaCode performed when pitted against human programmers, ranking in the top 54.3 percent in simulated tests, commensurate with “approximately human-level performance.” “This performance in competitions approximately corresponds to a novice programmer with a few months to a year of training,” according to Science, which says about half the humans who compete in coding contests could outperform the AI. Continue reading Deepmind’s AlphaCode AI Can Program Like Human Coders

Alphabet’s AI offshoot DeepMind has created an AI tool called Dramatron that can help co-write scripts, generating things like plot points, character and location descriptions and dialogue. While a human will still need to manage the process by editing and rewriting Dramatron’s suggestions, the app is designed to make the screenwriting process faster and easier. To deploy Dramatron, users will need an OpenAI API key and, ideally, a Perspective API key to minimize the risk of “offensive text.” In addition to AI researchers, DeepMind tested the tool with 15 playwrights and screenwriters who used it to co-write scripts. Continue reading DeepMind Tool Provides AI-Powered Screenplay Assistance

Nvidia has issued a software update for its formidable NeMo Megatron giant language training model, increasing efficiency and speed. Barely a year since Nvidia unveiled Megatron, this latest improvement further leverages the transformer engine architecture that has become synonymous with deep learning since Google introduced the concept in 2017. New features result in what Nvidia says is a 5x reduction in memory requirements and up to a 30 percent gain in speed for models as large as 1 trillion parameters, making NeMo Megatron better at handling transformer tasks across the entire stack. Continue reading Nvidia Turbo Charges NeMo Megatron Large Training Model

Data centers can be hazardous to the workers that build and maintain them, with exposure to live electrical wires and dangerous chemicals part of the job. Now tech firms including Microsoft and Meta Platforms are exploring how artificial intelligence can be used to make data centers safer for employees. Microsoft is working on an AI system that triggers alerts to prevent or mitigate dangerous incidents, while Meta is also analyzing ways AI can optimize data centers operating under extreme environmental conditions in order to prevent safety hazards. Continue reading Big Tech Taps AI to Advance Data Center Safety, Efficiency

Alphabet-backed research lab DeepMind last week released a new AI system called Gato that takes a step toward artificial general intelligence, or AGI, technology that enables machines to undertake and learn the same tasks as humans. Described by DeepMind as a “general purpose AI, Gato’s debut coincides with LinkedIn co-founder Reid Hoffman and DeepMind co-founder Mustafa Suleyman securing $225 million to fund Inflection AI, an artificial intelligence company the pair launched earlier this year to simplify communication between humans and computers. Neither investors nor valuation were disclosed. Continue reading DeepMind’s Gato Moves Toward Artificial General Intelligence

Nvidia CEO Jensen Huang announced a host of new AI tech geared toward data centers at the GTC 2022 conference this week. Available in Q3, the H100 Tensor Core GPUs are built on the company’s new Hopper GPU architecture. Huang described the H100 as the next “engine of the world’s AI infrastructures.” Hopper debuts in Nvidia DGX H100 systems designed for enterprise. With data centers, “companies are manufacturing intelligence and operating giant AI factories,” Huang said, speaking from a real-time virtual environment in the firm’s Omniverse 3D simulation platform. Continue reading Nvidia Introduces New Architecture to Power AI Data Centers

A new AI revolution is underway, turning people who know little about coding into developers. Called “no code,” startups are emerging to productize this new category, which essentially lets people use familiar, clickable web interfaces and even natural language to automate tasks or create simple applications, while machine learning takes over the rest. Proponents predict it will be a game-changer, powering a brigade of “citizen developers” to leverage artificial intelligence without knowing how to write code. Startups entering the space include Juji, which makes creating AI chatbots as easy as programming PowerPoint. Continue reading No-Code AI and Prediction Tools Bring Coding to the People

To understand speech visually, by reading lips, in addition to aurally, is an advantage for which AI has been waiting, according to researchers at Meta Platforms (formerly Facebook). The company says it has developed a framework that learns by watching — Audio-Visual Hidden Unit BERT (AV-HuBERT) — and that it is 75 percent more accurate than competing automated speech recognition systems on several metrics. Meta claims that AV-HuBERT outperforms the former best audiovisual speech recognition system with only one-tenth the inuput, which makes it potentially useful with languages with little or no audio data. Continue reading Companies Turn to AI for New Approaches to Audio Solutions

Advances in language comprehension for artificial intelligence are issuing from San Francisco’s OpenAI and London-based DeepMind. OpenAI, which has been working on large language models, says it now lets customers fine-tune its GPT-3 models using their own custom data, while the Alphabet-owned DeepMind is talking-up Gopher, a 280-billion parameter deep-learning language model that has scored impressively on tests. Sophisticated language models have the ability to comprehend natural language, as well as predict and generate text, requirements for creating advanced AI systems that can dispense information and advice or that are required to follow instructions. Continue reading Advances by OpenAI and DeepMind Boost AI Language Skills

Samsung is using Synopsys’ DSO.ai tool to design some of its next-gen Exynos mobile processors for 5G and AI, which will be used in smartphones including its own and other devices. Synopsys chair and co-chief executive Aart de Geus said this is the first example of a “real commercial processor design with AI.” Google, IBM and Nvidia are among the other companies that have discussed designing chips with AI. Synopsys, which works with dozens of companies, also has years of expertise in creating advanced designs to train an AI algorithm. Continue reading Samsung First to Design Commercial Semiconductor with AI

Facebook introduced an AI text-to-speech system (TTS) that produces a second of audio in 500 milliseconds. According to Facebook, the system, which is used with a new approach to data collection, powered the creation of a British accent-inflected voice in six months, versus over a year required for other voices. The TTS is now used for Facebook’s Portal smart display brand. The system can be hosted in real time via ordinary processors and is also available as a service for other apps, including Facebook’s VR. Continue reading Facebook Reveals New AI-Powered Text-to-Speech System