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Category: robotics/AI – Page 791

The more competition the better. Download and spread around the world so large companies cant seal away competition under a cloak of AI safety.

Meta, the company formerly known as Facebook, has recently announced that it is open-sourcing its large language model (LLM) called LLaMA 2, making it free for commercial and research use. This move is seen as a direct challenge to OpenAI’s ChatGPT, the popular chatbot powered by the GPT-4 model, which is not open-sourced and requires a subscription fee to access.

LLaMA 2 is a generative AI model that can produce natural language texts based on a given input or prompt. It can be used for various applications such as chatbots, content creation, summarization, translation, and more. LLaMA 2 is the second version of Meta’s LLM, which was first released in February 2023. According to Meta, LLaMA 2 was trained on 40% more data than LLaMA 1, which includes information from “publicly available online data sources”. It also claims that it “outperforms” other LLMs like Falcon and MPT when it comes to reasoning, coding, proficiency, and knowledge tests.

Meta decided to make LLaMA 2 available for free through Microsoft’s Azure platform, as well as other providers such as AWS, Hugging Face, and direct download. Meta said that it wants to give businesses, startups, and researchers access to more AI tools, allowing for experimentation and innovation as a community. Meta also said that it is committed to “building responsibly” as it moves forward with its AI system. The company said its models have been tested for safety by “generating adversarial prompts to facilitate model fine-tuning”, both internally and externally. Meta also discloses how the models are evaluated and tweaked.

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No surprise. Already moving to make AI a subscription service like subscriptions to movie studios. But, i actually see it as a positive. 1. The Best AI service will have to put up or shut up and market will decide it; no more role play of who s the best. 2. Real customer service; no more, o you have a tec issue, sorry, get lost. 3. Funds and competition will force improvements.

Microsoft’s one-day gain in market value is more than the entire valuation of about 450 S&P 500 companies.

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A proton-driven approach that enables multiple ferroelectric phase transitions sets the stage for ultralow power, high-capacity computer chips.

A proton-mediated approach that produces multiple in could help develop high-performance memory devices, such as brain-inspired, or neuromorphic, computing chips, a KAUST-led international team has found. The paper is published in the journal Science Advances.

Ferroelectrics, such as indium selenide, are intrinsically polarized materials that switch polarity when placed in an , which makes them attractive for creating memory technologies. In addition to requiring low operating voltages, the resulting memory devices display excellent maximum read/write endurance and write speeds, but their storage capacity is low. This is because existing methods can only trigger a few ferroelectric phases, and capturing these phases is experimentally challenging, says Xin He, who co-led the study under the guidance of Fei Xue and Xixiang Zhang.

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Intel’s investment arm has invested $9 million in Figure, a company specialising in humanoid robots for general purpose.

Here’s What We Know

Figure caught the attention of the robotics industry due to its success in creating a general-purpose robot. Just a few months after its inception, the company unveiled the humanoid Figure 01.

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This could help us improve our understanding of the Sun and its impact on space weather.

A collaborative effort between researchers at the University of Graz in Austria and the Skolkovo Institute of Science and Technology (Skoltech) in Russia used artificial intelligence (AI) to study the magnetic field in the upper atmosphere of the Sun, a press release said.

The solar magnetic field is a poorly understood area of research among astronomers. Even after centuries of watching the Sun, we only have limited information about how sunspots are formed or whether they will lead to events like a flare or a coronal mass ejection (CME).

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Artificial intelligence is rapidly changing our lives for the better making it easier, better, more entertaining, and, hopefully, longer and healthier. Between 2013 and 2014, advances in deep learning led to machines outperforming humans in image recognition, text recognition, voice recognition and many other tasks. The generative AI revolution, which, despite the many early proof-of-concept papers, went mainstream after the publication of the Generative Adversarial Networks (GANs) in 2014 and Transformers in 2017, has led to the creation of many advanced generative tools and apps that are transforming our lives in the most profound way possible. Many predictions made by Jensen Huang, the prolific CEO of NVIDIA — a company that has enabled and powered the AI revolution, have come true and even exceeded expectations. Instructional Transformer-based Large Language Models (LLMs) like ChatGPT are already in mainstream use. ChatGPT can already outperform me in the many writing tasks, and we even co-authored an academic paper. Today, there are millions of professionals working on the development of AI systems and applications. Many of these professionals, including the author of this article, would very likely celebrate ‘International AI Day’ if there were one.

On July 16th, social media lit up with the celebratory posts for the “AI Appreciation Day” often using the #AIAppreciationDay hashtag. Several large brands and academic institutions, including Zeiss, Wistar Institute, and MBZUAI followed.

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MicroNeuro ensures surgical safety and frees surgeons from labor-intensive tasks.

Today, less than 3 surgeries in the world are robot-assisted. The most common type of clinical robotic surgical system surgeons use includes a camera and mechanical arms with surgical instruments attached to them.

Robot assistance is known to provide more precision in brain surgeries than humans performing surgery, which may lead to damage to healthy tissues.

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Queen Mary University researchers have engineered a self-sensing, variable-stiffness artificial muscle that mimics natural muscle characteristics. The breakthrough has significant implications for soft robotics and medical applications, moving a step closer to human-machine integration.

In a study published on July 8 in Advanced Intelligent Systems, researchers from Queen Mary University of London have made significant advancements in the field of bionics with the development of a new type of electric variable-stiffness artificial muscle that possesses self-sensing capabilities. This innovative technology has the potential to revolutionize soft robotics and medical applications.

Technology Inspired by Nature.

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