Understanding AI agents with Anthropic’s playbook: what they are, what they can do for your business, and how to set one up. Automate your way to success and freedom.
Category: robotics/AI – Page 7
Kaiming He, a professor in the Department of Electrical Engineering and Computer Science, believes AI can create a common language that lowers barriers between scientific fields and fosters collaboration across scientific disciplines.
“There is no way I could ever understand high-energy physics, chemistry, or the frontier of biology research, but now we are seeing something that can help us to break these walls,” said He.
MIT Associate Professor Kaiming He discusses the role of AI in interdisciplinary collaborations, connecting basic science to artificial intelligence, machine learning, and neural networks.
The question is, can DEI proponents, who are already being marginalized, retool? Can they see themselves as champions who will guide humanity — regardless of peoples’ race, class, sexual orientation, gender, etc. — in this Fourth Industrial Revolution?
For, if political leaders are as unable as they seem to establish meaningful guardrails, AI will push those struggling to live their best lives (a right that should belong to all) to be thrown so far under the bus that roadkill will be more recognizable.
A robotic labor force.
Engineering companies in China have begun the process of starting full-scale mass production of humanoid robots in anticipation of a commercial boom in 2025. Companies such as Shanghai Zhiyuan Innovation Technology (AgiBot) and Shanghai Kepler Robot Company have already been testing the robots to optimize performance while reducing production costs.
With Google’s latest AI model, Gemini 2.0, launched in December, the company is making big moves in AI. Brin’s message is clear, the race to AGI is on, and Google plans to win it.
In today’s AI news, Meta, the parent company of Facebook, and other leading social media platforms, is looking to raise as much as $35 Billion to build data centers in the US. Apollo Global Management Inc., an alternative asset manager has discussed providing a major part of the financing, said the people, who asked not to be identified. KKR & Co. is also a part of the investor group.
In other advancements, With so much software now getting written by AI, having a window into its security can be a challenge. That’s the premise of Archipelo, a San Francisco-based cybersecurity startup that is today emerging from stealth with $12 Million in funding. Archipelo’s pitch is that it has a platform for “Developer Security Posture Management” (DevSPM).
S integration with Suno, you can turn simple, creative requests into songs. ‘ + And, In its annual letter, payments giant Stripe declared that it was “seeing an AI boom” with its data, revealing that artificial intelligence startups are growing more rapidly than traditional SaaS companies have historically. In a chart, Stripe showed that the top 100 AI companies were able to achieve $5 million in annualized revenue in 24 months in 2024 compared to the top 100 SaaS companies taking 37 months.
In videos, ever wondered how to enhance your AI performance? IBM’s Susan Eickhoff shows how to boost AI performance using an ensemble of models, combining traditional AI and large language models. Learn structured data analysis and dynamic prediction methods.
And, since its launch in 2020, Project Aria has propelled research across the world to advance the state of the art in machine perception and AI, through access to cutting-edge research hardware and open-source datasets, models, and tooling. Today, Meta is excited to announce the next step in this journey: the introduction of Aria Gen 2 glasses.
In our creative writing tests—designed to measure how well these models craft engaging stories that actually make sense—Claude 3.7 delivered narratives with more human-like language and better overall structure than its competitors.
Think of these tests as measuring how useful these models might be for scriptwriters or novelists working through writer’s block.
While the gap between Grok-3, Claude 3.5, and Claude 3.7 isn’t massive, the difference proved enough to give Anthropic’s new model a subjective edge.
Researchers from three of Virginia’s premier universities, including the University of Virginia’s Homa Alemzadeh, aim to take the risk out of self-driving vehicles by overcoming inevitable computer failures with sound engineering.
Cutting-edge research from three top Virginia universities, led by the University of Virginia’s Homa Alemzadeh, is on a mission to revolutionize the safety of self-driving vehicles. With a substantial $926,737 grant from the National Science Foundation, this powerhouse team is dedicated to pinpointing and neutralizing potential computer failures in autonomous vehicle systems.
By harnessing this insight, they aim to fortify the resilience of the entire system and proactively eliminate safety risks. Alemzadeh, a trailblazing associate professor of electrical and computer engineering at UVA’s School of Engineering and Applied Science, is joined by the esteemed William & Mary professor of computer science, Evgenia Smirni, and the visionary lead investigator and George Mason University assistant professor of computer science, Lishan Yang.
Dr. Rumi Chunara: “Our system learns to recognize more subtle patterns that distinguish trees from grass, even in challenging urban environments.”
How can artificial intelligence (AI) help improve city planning to account for more green spaces? This is what a recent study published in the ACM Journal on Computing and Sustainable Societies hopes to address as a team of researchers proposed a novel concept using AI with the goal of both monitoring and improving urban green spaces, which are natural public spaces like parks and gardens, and provide a myriad of benefits, including physical and mental health, combating climate change, wildlife habitats, and increased social interaction.
For the study, the researchers developed a method they refer to as “green augmentation”, which uses an AI algorithm to analyze Google Earth satellite images with the goal of improving current AI methods by more accurately identifying green vegetation like grass and trees under various weather and seasonal conditions. For example, current AI methods identify green vegetation with an accuracy and reliability of 63.3 percent and 64 percent, respectively. Using this new method, the researchers successfully identified green vegetation with an accuracy and reliability of 89.4 percent and 90.6 percent, respectively.
“Previous methods relied on simple light wavelength measurements,” said Dr. Rumi Chunara, who is an associate professor of biostatistics at New York University and a co-author on the study. “Our system learns to recognize more subtle patterns that distinguish trees from grass, even in challenging urban environments. This type of data is necessary for urban planners to identify neighborhoods that lack vegetation so they can develop new green spaces that will deliver the most benefits possible. Without accurate mapping, cities cannot address disparities effectively.”