Category robots

Breakthrough models AlphaProof and AlphaGeometry 2 solve advanced reasoning problems in mathematics

Self-amputation may seem like a drastic move, but it's a survival tactic that's proved particularly handy for numerous creatures. Yale roboticists have drawn inspiration from lizards, crabs, and other animals who shed parts of themselves without looking back, all for the purpose of moving forward.

Engineers have shown that something as simple as the flow of air through open-cell foam can be used to perform digital computation, analog sensing and combined digital-analog control in soft textile-based wearable systems.

Self-driving cars occasionally crash because their visual systems can't always process static or slow-moving objects in 3D space. In that regard, they're like the monocular vision of many insects, whose compound eyes provide great motion-tracking and a wide field of view but poor depth perception.

Using a newly-devised complex algorithm, the researchers have created a perfectly choreographed "dance" using two robotic arms, continuously retaining a clear space between them—where a patient's body would fit—as well as ensuring a consistent magnetic field.

Carnegie Mellon University researchers at the Biohybrid and Organic Robotics Group (B.O.R.G.) led by Victoria Webster-Wood, in collaboration with researchers at Case Western Reserve University, are studying the sea slug feeding structure to learn more about how the brain, muscular system and nervous system interact. Their research is being used both in robots and in simulations as part of a multinational research collaboration studying neuromuscular systems.

Humans are interacting more than ever with artificial intelligence (AI)—from the development of the first "social robots" (a robot with a physical body programmed to interact and engage with humans) like Kismet in the 1990s to smart speakers such as Amazon's Alexa.

In a fast-growing environment, how does our small data science team continuously solve our company’s and customers’ greatest challenges?

At Razorpay, our mission is to be a one-stop fintech solution for all business needs. We power online payments and provide other financial solutions for millions of businesses across India and Southeast Asia.

Since I joined in 2021, we have acquired six companies and expanded our product offerings. 

Though we’re growing quickly, Razorpay competes against much larger organizations with significantly more resources to build data science teams from scratch. We needed an approach that harnessed the expertise of our 1,000+ engineers to create the models they need to make faster, better decisions. Our AI vision was fundamentally grounded in empowering our entire organization with AI. 

Fostering Rapid Machine Learning and AI Experimentation in Financial Services

Given our goal of putting AI into the hands of engineers, ease-of-use was at the top of our wish list when evaluating AI solutions. They needed the ability to ramp up quickly and explore without a lot of tedious hand-holding. 

No matter someone’s background, we want them to be able to quickly get answers out of the box. 

AI experimentation like this used to take an entire week. Now we’ve cut that time by 90%, meaning we’re getting results in just a few hours. If somebody wants to jump in and get an AI idea moving, it’s possible. Imagine those time savings multiplied across our entire engineering team – that’s a huge boost to our productivity. 

That speed allowed us to solve one of our toughest business challenges for customers:  fraudulent orders. In data science, timelines are usually measured in weeks and months, but we achieved it in 12 hours. The next day we went live and blocked all malicious orders without affecting a single real order. It’s pretty magical when your ideas become reality that fast and have a positive impact on your customers.

‘Playing’ with the Data

When team members load data into DataRobot, we encourage them to explore the data to the fullest – rather than rushing to train models. Thanks to the time savings we see with DataRobot, they can take a step back to understand the data relative to what they’re building.

That layer helps people learn how to operate the DataRobot Platform and uncover meaningful insights. 

At the same time, there’s less worry about whether something is coded correctly. When the experts can execute on their ideas, they have confidence in what they’ve created on the platform.

Connecting with a Trusted Cloud Computing Partner 

For cloud computing, we’re a pure Amazon Web Services shop. By acquiring DataRobot via the AWS marketplace, we were able to start working with the platform within a day or two. If this had taken a week, as it often does with new services, we would have experienced a service outage.

The integration between the DataRobot AI Platform and that broader technology ecosystem ensures we have the infrastructure to tackle our predictive and generative AI initiatives effectively.

Minding Privacy, Transparency, and Accountability

In the highly regulated fintech industry, we have to abide by quite a few compliance, security, and auditing requirements.

DataRobot fits our demands with transparency, bias mitigation, and fairness behind all our modeling. That helps ensure we’re accountable in everything we do.

Standardized Workflows Set the Stage for Ongoing Innovation 

For smoother adoption, creating standard operating procedures has been critical. As I experimented with DataRobot, I documented the steps to help my team and others with onboarding.

What’s next for us? Data science has changed dramatically in the past few years. We’re making decisions better and quicker as AI moves closer to how humans behave. 

What excites me most about AI is it’s now fundamentally an extension of what we’re trying to achieve – like a co-pilot. 

Our competitors are probably 10 times bigger than us in terms of team size. With the time we save with DataRobot, we now have the opportunity to get ahead. The platform is an extreme developer productivity multiplier that allows our existing experts to prepare for the next generation of engineering and quickly deliver value to our customers. 

The post Customer Spotlight: Building a Competitive & Collaborative AI Practice in FinTech appeared first on DataRobot.

Most robotic systems developed to date can either tackle a specific task with high precision or complete a range of simpler tasks with low precision. For instance, some industrial robots can complete specific manufacturing tasks very well but cannot easily adapt to new tasks. On the other hand, flexible robots designed to handle a variety of objects often lack the accuracy necessary to be deployed in practical settings.

With this latest raise, the company behind the world's first fully electric, driver-optional, smart tractor cements its position as a leader in the space

An international collaboration seeks to innovate the future of how a mechanical man's best friend interacts with its owner, using a combination of AI and edge computing called edge intelligence. The overarching project goal is to make the dog come 'alive' by adapting wearable-based sensing devices that can detect physiological and emotional stimuli inherent to one's personality and traits, such as introversions, or transient states, including pain and comfort levels.

The introduction of the automobile changed American culture profoundly, and it has been doing so for over a century. Innovations in automotive technology have allowed people to travel farther, faster, and for less fuel than generations before. In fact, the […]

The post 5 Ways AI Is Revolutionizing the Automotive Industry appeared first on TechSpective.

An automated assessment technique that uses artificial intelligence could revolutionize the management of Parkinson's disease.

PI presented a new, high-speed hexapod at the International Aerospace Exhibition ILA Berlin in June 2024, as a partner in the LuFo VI-1: ADMAS (Advanced Machining and Sealing) research project.

Researchers are calling for regulation to guide the responsible and ethical development of bio-hybrid robotics -- a ground-breaking science which fuses artificial components with living tissue and cells.