Think of it as a ChatGPT service for images.
Category: robotics/AI – Page 1,085
Google’s cloud business turns profitable for the first time on record
Google has been vying to win business from big corporations and government agencies that are deciding between major tech vendors as they move from traditional data centers to the cloud and rely on more compute-heavy applications involving artificial intelligence. Amazon Web Services, the leader in cloud infrastructure, popularized the market in the mid-2000s and has been profitable every quarter since 2014. Microsoft, the second-biggest player in the space, doesn’t report profitability figures for its Azure unit.
Alphabet started disclosing cloud revenue in 2020, and the following year began providing information on the scale of its operating losses.
Last week Alphabet restated operating income for cloud and its other segments, resulting in lower cloud losses in 2021 and 2022. The restated numbers show the cloud unit had a $186 million operating loss in the fourth quarter, compared with $480 million before the change, for example.
Microsoft outperforms Google in Q1 as AI set to take center-stage
Its partnership with OpenAI gives Microsoft a head start.
After years of playing second fiddle to Google in the search engine market, Microsoft is set to become a technology leader again as businesses and individuals worldwide look to incorporate artificial intelligence (AI) into everything they do. In the Q1 2023 earnings reported recently, the 48-year-old company has outperformed its younger rival, Alphabet.
For years, Microsoft was mainly a market leader in operating systems. Still, the changing nature of computing technologies meant it has ventured into other areas, such as cloud computing and gaming, through its Xbox platform.
China’s NetEase launches ChatGPT rival that builds apps with text prompts
CodeWave’s platform generates the code necessary to develop the app from descriptions of the users’ intended app functionality.
One of China’s largest video gaming companies, NetEase, has introduced CodeWave, a “low-code” application development platform powered by its large language model (LLM).
This makes NetEase, the newest major Chinese tech company, to provide such artificial intelligence (AI) service, allowing users “to build apps with text prompts,” according to a new report by South China Morning Post (SCMP) on Wednesday.
Mark Zuckerberg says Meta wants to “introduce AI agents to billions of people”
‘I expect that these tools will be valuable for everyone from regular people to creators to businesses.’
Meta sees “an opportunity to introduce AI agents to billions of people in ways that will be useful and meaningful,” CEO Mark Zuckerberg told investors today.
While he was vague about how exactly Meta will add generative AI to its apps, Zuckerberg gave the most detailed preview yet during the company’s earnings call for the first quarter of this year, when it reported $28.6 billion in revenue and a record 2 billion daily users of the Facebook app, beating Wall Street’s estimates. Meta’s profit for the quarter was $5.7 billion, a 24 percent decrease from the same time last year.
Get ready for ChatGPT competition in Instagram, Facebook, and WhatsApp.
Three ways AI chatbots are a security disaster
Greshake hid a prompt on a website that he had created. He then visited that website using Microsoft’s Edge browser with the Bing chatbot integrated into it. The prompt injection made the chatbot generate text so that it looked as if a Microsoft employee was selling discounted Microsoft products. Through this pitch, it tried to get the user’s credit card information. Making the scam attempt pop up didn’t require the person using Bing to do anything else except visit a website with the hidden prompt.
In the past, hackers had to trick users into executing harmful code on their computers in order to get information. With large language models, that’s not necessary, says Greshake.
Call for Papers (Students)
Copied from :- https://www.facebook.com/francesca.rossi.
Are you a PhD student working on AI ethics? The 6th AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (AIES) invites PhD students to apply for the AIES student track, which offers targeted programming, mentorship, and funding to attend AIES in Montreal from August 8–10, 2023. We welcome all disciplines, methods, and backgrounds and strongly encourage applications from underrepresented and/or minoritized students.
Deadline: May 12, 2023
The AIES student track is a competitive program that provides PhD students with targeted programming, mentorship, and financial support to attend AIES. In addition to attending the conference, accepted students present their research in a lightning talk and poster session, participate in breakout groups with peers, and receive mentoring from senior scholars.
All PhD students with research interests relevant to the conference are welcome to apply, whether or not they have already submitted a paper to the main track of AIES. (See the main track CFP for the full list of research topics.) Students with papers already accepted by the main track must make a separate application if they wish to be considered for the student program.
Acceptance into the student program will include both free conference registration and a travel stipend to significantly offset travel and accommodation costs. The precise award amount will vary according to financial need.
Neural Nanotechnology: Nanowire Networks Learn and Remember Like a Human Brain
Scientists have demonstrated that nanowire networks can exhibit short-and long-term memory, similar to the human brain. These networks, comprised of highly conductive silver wires covered in plastic and arranged in a mesh-like pattern, mimic the physical structure of the human brain. The team successfully tested the nanowire network’s memory capabilities using a task similar to human psychology experiments. This breakthrough in nanotechnology suggests that non-biological hardware systems could potentially replicate brain-like learning and memory, and has numerous real-world applications, such as improving robotics and sensor devices in unpredictable environments.
In a groundbreaking study, an international team has shown that nanowire networks can mimic the short-and long-term memory functions of the human brain. This breakthrough paves the way for replicating brain-like learning and memory in non-biological systems, with potential applications in robotics and sensor devices.
An international team led by scientists at the University of Sydney has demonstrated nanowire networks can exhibit both short-and long-term memory like the human brain.
First Babies Born After Being Conceived By Robot
A Spanish startup has built a sperm-injecting robot that can be controlled using a PlayStation controller. The team successfully used it to fertilize human eggs, eventually resulting in the birth of two healthy babies.
As MIT Technology Review reports, one of the engineers working on the world’s first insemination robot didn’t have all that much experience in the field of fertility medicine — which was where the PlayStation 5 controller came into, well, play.
Using the controller, a student engineer from startup Overture Life [name after descriptor] steered a tiny, mechanized in-vitro fertilization (IVF) needle to deposit single sperm cells into human eggs more than a dozen times.
Polybot: AI and robotics unite to revolutionize polymer electronics research
A team of researchers at the U.S. Department of Energy’s Argonne National Laboratory has developed a new scientific tool called Polybot that combines artificial intelligence with robotics. This tool is set to revolutionize polymer electronics research by speeding up the discovery process of materials with multiple applications, from wearable biomedical devices to better batteries, according to a release.
Polymer electronics are the future of flexible electronics. They are efficient and sustainable, used to monitor health and treat certain diseases, among other things. However, the current methods used to prepare these polymers for electronics can take years of intense labor. To achieve targeted performance, there are an overwhelming number of potential tweaks, from spiking the fabrication recipe with different formulations to varying the processing conditions.