If Google's generative AI Gemini Assistant chatbot is to surpass OpenAI's ChatGPT in popularity in the coming years, it may have to do so without some of the promotional partnerships that helped thrust Google search front and center into Americans' lives. In a US federal court filing on Friday, Google proposed a series of restrictions that for three years would bar the company from requiring its device manufacturer, browser, and wireless carrier licensees to distribute Gemini to their US users. Google also would give those partners more flexibility in how they set their default search provider for their users. Google's proposal counters last month's call from the US Justice Department for Google to not only loosen its grip over partners, but also share more data with competitors and divest its Chrome browser business. The company on Friday formally rejected the idea of selling off any piece of its business or turning over more information to rivals. And its proposed restrictions could be construed as narrower than those sought by the government.

In the paper released earlier this week, Google explained how it connected over 4,000 TPUs to create a supercomputer. Google claims the supercomputers used for training its artificial intelligence (AI) models are faster and more energy-efficient than those employed by multinational technology firm Nvidia. Google researchers detailed how they created a supercomputer from more than 4,000 fourth-generation Tensor Processing Units (TPUs), as well as custom optical switches to link individual machines. The AI models are segmented across thousands of chips, which must collaboratively train the models for weeks or more. Google's Norm Jouppi and David Patterson explained, "Circuit switching makes it easy to route around failed components. This flexibility even allows us to change the topology of the supercomputer interconnect to accelerate the performance of an ML (machine learning) model."

Artificial intelligence researchers are doubling down on the concept that we will see artificial general intelligence (AGI) -- that's AI …

Artificial intelligence researchers are doubling down on the concept that we will see artificial general intelligence (AGI) -- that's AI that can accomplish anything humans can, and probably many we can't -- within our lifetimes. Responding to a pessimistic op-ed published by TheNextWeb columnist Tristan Greene, Google DeepMind lead researcher Dr. Nando de Freitas boldly declared that "the game is over" and that as we scale AI, so too will we approach AGI. Greene's original column made the relatively mainstream case that, in spite of impressive advances in machine learning over the past few decades, there's no way we're gonna see human-level artificial intelligence within our lifetimes. But it appears that de Freitas, like OpenAI Chief Scientist Ilya Sutskever, believes otherwise. "Solving these scaling challenges is what will deliver AGI," the DeepMind researcher tweeted, later adding that Sutskever "is right" to claim, quite controversially, that some neural networks may already by "slightly conscious."

A team of Google researchers has used a deep-learning algorithm to predict lung cancer accurately from computed scans. The work demonstrates the potential for Artificial Intelligence (AI) to increase both accuracy and consistency, which could help accelerate adoption of lung cancer screening worldwide. Lung cancer is the deadliest of all cancers worldwide -- more than breast, prostate, and colorectal cancers combined -- and it's the sixth most common cause of death globally, according to the World Health Organization. "Using advances in 3D volumetric modelling alongside datasets from our partners (including Northwestern University), we've made progress in modelling lung cancer prediction as well as laying the groundwork for future clinical testing," Shravya Shetty, M.S. Technical Lead at Google explained in a blog post late Monday. Google researchers created a model that can not only generate the overall lung cancer malignancy prediction (viewed in 3D volume) but also identify subtle malignant tissue in the lungs (lung nodules).

Google said it has built a computer that's reached "quantum supremacy," performing a computation in 200 seconds that would take the fastest supercomputers about 10,000 years. The results of Google's tests, which were conducted using a quantum chip it developed in-house, were published Wednesday in the scientific journal Nature. "This achievement is the result of years of research and the dedication of many people," Google engineering director Hartmut Neven said in a blog post. "It's also the beginning of a new journey: figuring out how to put this technology to work. We're working with the research community and have open-sourced tools to enable others to work alongside us to identify new applications."

In a Webmaster Hangout, an eCommerce publisher complained about structured data warnings regarding data fields that are inappropriate to their product. They refused to create fake information to get a passing score. John Mueller responded that there's a difference between warnings and errors. The person asking the question sold custom hand made products. They did not have a global identifier.

Last April, Google cofounder Sergey Brin wrote to shareholders with a warning about the potential downsides of artificial intelligence. In June, Google CEO Sundar Pichai released a set of guiding principles for its AI projects after employee protests forced him to abandon a Pentagon contract creating algorithms to interpret drone footage. Now Google has released a white paper that asks governments to suggest some rules for AI--but please, not too many! As you might expect, the 30-page document Google released last week extols the power of artificial intelligence. "AI can deliver great benefits for economies and society, and support decision making which is fairer, safer and more inclusive and informed," it says.

Google software engineer Cliff Young says the use of artificial intelligence has reached an "exponential phase" at the very same time that Moore's Law has ground to a standstill. The explosion of AI and machine learning is changing the very nature of computing, so says one of the biggest practitioners of AI, Google. Google software engineer Cliff Young gave the opening keynote on Thursday morning at the Linley Group Fall Processor Conference, a popular computer-chip symposium put on by venerable semiconductor analysis firm The Linley Group, in Santa Clara, California. Said Young, the use of AI has reached an "exponential phase" at the very same time that Moore's Law, the decades-old rule of thumb about semiconductor progress, has ground to a standstill. "The times are slightly neurotic," he mused.

Houston, Texas, USA: Google on Friday claimed that its AI algorithm can assist doctors in metastatic breast cancer detection with 99 percent accuracy, according to their papers published in the Archives of Pathology and Laboratory Medicine and The American Journal of Surgical Pathology. The algorithm technology, known as Lymph Node Assistant, or LYNA, is taught to check the abnormality in the pathology slides and accurately pinpoint the location of both cancers and other suspicious regions since some of the potential risks are too small to be spotted by the doctors. In their latest research, Google applied LYNA to a de-identified dataset from both Camelyon Challenge and an independent dataset from the Naval Medical Center San Diego for picking up the cancer cells from the tissue images. Metastatic tumors -- cancerous cells which break away from their tissue of origin, travel through the body through the circulatory or lymph systems, and form new tumors in other parts of the body -- are notoriously difficult to detect. A 2009 study of 102 breast cancer patients at two Boston health centers found that one in four were affected by the "process of care" failures such as inadequate physical examinations and incomplete diagnostic tests.