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Category: robotics/AI – Page 820

Cofounder of Zeda.io—helping product leaders discover the right problems to solve and build around. And I love traveling, with my dog!

Artificial intelligence (AI) is transforming the world as we know it, and product management is no exception. It has the potential to revolutionize customer research, decision-making and much more, providing us with data-driven insights and paving the way for a future that is not only intelligent but intuitive.

With AI at our fingertips, we’re standing at the threshold of a new era in product management. However, integrating AI into product management also presents challenges that must be addressed. We will delve into how AI influences the world of product management and what it holds for the future.

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Andreessen argues that thanks to A.I., “productivity growth throughout the economy will accelerate dramatically, driving economic growth, creation of new industries, creation of new jobs, and wage growth, and resulting in a new era of heightened material prosperity across the planet.”

This week, on the Lex Fridman Podcast, he offered advice to young people who want to stand out in what he describes in this “freeze-frame moment” with A.I.—where tools like ChatGPT and GPT-4 are suddenly available and “everybody is kind of staring at them wondering what to do.”

He noted that we’re now living in a world where vast amounts of information are at our fingertips and, with A.I. tools, “your ability both to learn and to produce” is dramatically higher than in the past. Such tools should allow for more “hyper-productive people” to emerge, he said. For example, there’s no reason authors and musicians couldn’t churn out far more books or songs than was customary in the past.

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Huge libraries of drug compounds may hold potential treatments for a variety of diseases, such as cancer or heart disease. Ideally, scientists would like to experimentally test each of these compounds against all possible targets, but doing that kind of screen is prohibitively time-consuming.

In recent years, researchers have begun using computational methods to screen those libraries in hopes of speeding up drug discovery. However, many of those methods also take a long time, as most of them calculate each target protein’s three-dimensional structure from its amino-acid.

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Researchers in Japan and Australia have developed a new multicore optic fiber able to transmit a record-breaking 1.7 petabits per second, while maintaining compatibility with existing fiber infrastructure. The team–from Japan’s National Institute of Information and Communications Technology (NICT) and Sumitomo Electric Industries, and Macquarie University in Sydney, Australia—achieved the feat using a fiber with 19 cores. That’s the largest number of cores packed into a cable with a standard cladding diameter of 0.125 micrometers.

“We believe 19 cores is the highest practical number of cores or spatial channels you can have in standard cladding diameter fiber and still maintain good quality transmission,” says Georg Rademacher, who previously headed the project for NICT but who has recently returned to Germany to take up a directorship in optical communications at the University of Stuttgart.

Most fiber cables for long-distance transmission in use today are single core, single-mode glass fibers (SMF). But SMF is approaching its practical limit as network traffic rapidly increases because of AI, cloud computing, and IoT applications. Many researchers are therefore taking an interest in multicore fiber in conjunction with space-division multiplexing (SDM), a transmission technique for using multiple spatial channels in a cable.

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Some of the world’s leading human and robot minds are heading to the United Nations.

At a UN summit in Geneva next week, tech luminaries ranging from futurist Ray Kurzweil to DeepMind COO Lila Ibrahim will discuss AI for good. It’s a stellar lineup of speakers, but the real stars in our eyes are the robots.

Over 50 of the beasts — the majority from Europe — will be in attendance. All of them merit places in your dreams and nightmares, but we’ve narrowed the roster down to a list of our 10 favourites.

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I’d place Sigmund et al. as one of my favorite papers that I have read this year! They leverage protein engineering to create genetically encoded nanocages which accumulate metals and appear as concentric circles when imaged by electron microscopy. Six classes of distinct “EMcapsulins” could be differentiated by training a machine learning model (a convolutional neural network) to recognize and classify them within images. Fusion of fluorescent protein domains to the EMcapsulins also allowed correlative imaging between fluorescence microscopy and electron microscopy. The authors demonstrated 3D imaging of EMcapsulins via serial section transmission electron microscopy and focused ion beam… More.

Multiplexable barcodes for electron microscopy are applied to brain imaging.

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TOKYO (Reuters) — What would society look like if cyborg body parts were freely available for use like roadside rental bicycles? Masahiko Inami’s team at the University of Tokyo have sought to find out by creating wearable robotic arms.

Inami’s team is developing a series of technologies rooted in the idea of “jizai”, an Japanese term that he says roughly denotes autonomy and the freedom to do as one pleases.

The aim is to foster something like the relationship between musician and instrument, “lying somewhere between a human and a tool, like how a musical instrument can become as if a part of your body.”

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With generative AI taking over the artificial intelligence world, it was only a matter of time before it came to the smart home. Josh.ai, a home automation system for the connected home, has officially launched JoshGPT.

Josh is here to replace your smart home automation system as your all-in-one solution — it says it’s got the brains that your current voice assistant can’t offer you.

This is just the first of likely many generative AI-enabled smart home platforms to come.

Continue reading “The first GPT-powered smart home platform is here” | >

The finance automation platform Ramp has acquired Cohere.io, an AI-powered customer support platform. The acquisition marks Ramp’s first foray into the world of generative AI, which is a sign of the growing importance of this technology in the finance industry. This is also a significant milestone for Ramp, as it is the company’s second acquisition since its inception in 2019 and the first since it purchased Buyer, a “negotiation-as-a-service” platform, in August of 2021.

Ramp is a technology business that specializes in corporate credit cards and cost management in the financial technology (fintech) sector. The company was founded in 2019 by Eric Glyman, Gene Lee, and Karim Atiyeh and is… More.

In addition to improving the quality of customer support, generative AI is also likely to lead to new innovations in customer support. For example, generative AI could be used to create chatbots that are capable of having natural conversations with customers. This could help businesses provide customer support 24/7 while reducing the cost of support.

Generative AI is a powerful technology that has the potential to revolutionize the customer support industry. The acquisition of Cohere.io by Ramp indicates that this revolution is already underway.

Continue reading “Ramp’s Acquisition Of Cohere.io Signals The Rise Of Generative AI In Customer Support” | >

The company plans to equip the chatbot with features that helped AlphaGo defeat a human Go champion.

DeepMind, previously considered the undisputed leader in the realm of artificial intelligence (AI) in the past decade, has now claimed that its next-generation AI model will surpass OpenAI’s ChatGPT. The revelation was made by company co-founder and CEO Demis Hassabis in an interview with Wired.

DeepMind first made global news when Google decided to acquire the software company in 2014. Back then, the company pioneered the use of reinforcement learning to train its AI models, a method that provides AI feedback on its performance. DeepMind started off by employing the approach of teaching AI how to play video games.

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