Newsrooms can potentially benefit greatly from AI language models, but at this early stage they’ve begun laying down boundaries to ensure that rather than having their data coopted to build artificial intelligence by third parties they’ll survive long enough to create models of their own, or license proprietary IP. As industries await regulations from the federal government, The New York Times has proactively updated its terms of service to prohibit data-scraping of its content for machine learning. The move follows a Google policy refresh that expressly states it uses search data to train AI. Continue reading The New York Times Looks to Protect IP Content in Era of AI

Meta Platforms has published a new AI technology, the Segment Anything Model (SAM) that the company claims can identify objects it hasn’t seen before. Acting on a text prompt, SAM will highlight items in a photo or video, picking out all the cats, for instance, or flowers. It can also execute other functions, such as generating a 3D construct using a single 2D image or extrapolating from things viewed in a mixed reality headset. Segment Anything can work in concert with other models, potentially minimizing the need for voluminous data sets for training. Continue reading New Meta AI Can Detect Objects It Has Not Been Trained On

After many years of academia leading the way in the development of artificial intelligence, the tides have shifted and industry has taken over, according to the 2023 AI Index, a report created by Stanford University with help from companies including Google, Anthropic and Hugging Face. “In 2022, there were 32 significant industry-produced machine learning models compared to just three produced by academia,” the report says. The shift in influence is attributed mainly to the large resource demands — in staff, computing power and training data — required to create state of the art AI systems. Continue reading Report: Enterprise Supplants Academia as Driving Force of AI

Google is introducing a new artificial intelligence app called MusicLM that creates music in any style or genre based on text prompts and can translate a whistled melody or casually hummed snipped into instrument sounds. TechCrunch calls the technology “impressive” but says the Alphabet company “fearing the risks, has no immediate plans to release it,” in recognition of the controversy surrounding AI models trained using copyrighted material. MusicLM was created using a dataset of 280,000 musical hours, resulting in the ability to generate minutes-long songs of “significant complexity.” Continue reading Google’s MusicLM AI Can Generate Tunes from Text Prompts

Wikimedia Enterprise has announced Google and the Internet Archive as its first customers. The Wikimedia Foundation launched the enterprise unit last year as a paid service for clients that source and reuse Wikipedia data at high volume. Google has been using Wikipedia content to fuel its search engine results. Wikimedia Enterprise clients have access to custom APIs that allow it to scrape and utilize data more efficiently and at greater scale. The service also provides guaranteed uptime and real-time content updates, minimizing outdated or inaccurate information. Continue reading Google Is the First Paying Customer of Wikimedia Enterprise

With the federal government still in the early phase of regulating artificial intelligence, cities and states are stepping in as they begin to actively deploy AI. While managing traffic patterns is straightforward, when it comes to policing and hiring practices, precautions must be taken to guard against algorithmic bias inherited from training data. The challenges are formidable. As with human reasoning, it is often difficult to trace the logic behind a machine’s decisions, making it challenging to identify a fix. Municipalities are evaluating different solutions, the goal being to prevent programmatic marginalization. Continue reading AI Laws Becoming Decentralized with Cities First to Regulate

OpenAI has created a new technology that creates and edits images based on written descriptions of the desired result. DALL-E 2, an homage to the surrealist painter Salvador Dalí and the Pixar film “Wall-E,” is still in development but is already producing impressive results with simple instructions like “kittens playing chess” and “astronaut riding a horse.” OpenAI says the tech, “isn’t being directly released to the public” and the hope is “to later make it available for use in third-party apps. “Already some are expressing worry that such a tool has potential to exponentially increase the use of deepfakes. Continue reading DALL-E 2 by OpenAI Creates Images Based on Descriptions

Transforming 2D objects into 3D ones is a challenge that has defeated numerous artificial intelligence labs, including those at Facebook, Nvidia and startup Threedy.ai. Now, a Microsoft Research team stated it has created the first “scalable” training technique to derive 3D models from 2D data. Their technology can, furthermore, learn to generate better shapes when trained exclusively with 2D images. The Microsoft team took advantage of software that produces images from display data, as featured in industrial renderers. Continue reading Microsoft Develops Scalable 2D-to-3D Conversion Technique