Engineer and adventurer Richard Jenkins has made oceangoing robots that could revolutionize fishing, drilling, and environmental science. His aim: a thousand of them.
Category: robotics/AI – Page 2,346
How Artificial Intelligence Could Help Us Live Longer
Insilico and its researchers are the first in the world to use GANs to generate molecules.
“The GAN technique is essentially an adversarial game between two deep neural networks,” as Alex explains.
While one generates meaningful noise in response to input, the other evaluates the generator’s output. Both networks thereby learn to generate increasingly perfect output.
Built for speed: DNA nanomachines take a (rapid) step forward
The smallest Imperial Walker to ever attack the rebel alliance.
When it comes to matching simplicity with staggering creative potential, DNA may hold the prize. Built from an alphabet of just four nucleic acids, DNA provides the floorplan from which all earthly life is constructed.
But DNA’s remarkable versatility doesn’t end there. Researchers have managed to coax segments of DNA into performing a host of useful tricks. DNA sequences can form logical circuits for nanoelectronic applications. They have been used to perform sophisticated mathematical computations, like finding the optimal path between multiple cities. And DNA is the basis for a new breed of tiny robots and nanomachines. Measuring thousands of times smaller than a bacterium, such devices can carry out a multitude of tasks.
In new research, Hao Yan of Arizona State University and his colleagues describe an innovative DNA walker, capable of rapidly traversing a prepared track. Rather than slow, tentative steps across a surface, the DNA acrobat cartwheels head over heels, covering ground 10- to 100-fold faster than previous devices.
How Robots Are Making Better Drugs, Faster
Companies like Eli Lilly & Co. and GlaxoSmithKline PLC are investing in automation with the hope of transforming drug discovery from an enterprise where humans do manual experiments to one where robots handle thousands of samples around the clock. This automation will be key to developing better therapies more efficiently, drug companies say, as research and development becomes more labor intensive amid the push toward more-tailored…
Is There a Smarter Path to Artificial Intelligence? Some Experts Hope So
The danger, some experts warn, is that A.I. will run into a technical wall and eventually face a popular backlash — a familiar pattern in artificial intelligence since that term was coined in the 1950s. With deep learning in particular, researchers said, the concerns are being fueled by the technology’s limits.
A branch of A.I. called deep learning has transformed computer performance in tasks like vision and speech. But meaning, reasoning and common sense remain elusive.
Longevity, the Greatest Investment Opportunity of All Time
The exponential potential of longevity technologies.
Jim Mellon became a billionaire by pouncing on a wide variety of opportunities, from the dawn of business privatization in Russia to uranium mining in Africa and real estate in Germany. But all of that might eventually look small, he says, compared to the money to be made in the next decade or so from biotechnologies that will increase human longevity well past 100.
The British investor is so enthusiastic about these technologies that he co-authored a 2017 book about them, Juvenescence: Investing in the Age of Longevity, and launched a company, Juvenescence Ltd., to capitalize on them. “Juvenescence” is a real word — it’s the state of being youthful. Says Mellon, who is 61: “I’m hoping that this stuff works on me as well as on my portfolio.”
Juvenescence Ltd., which has raised $62.5 million from Mellon and some partners, has invested in or is close to confirming investments in nine biotech companies. He won’t discuss most of them. But one of the deals was an 11 percent stake in Insilico Medicine, a company applying machine-learning techniques to drug discovery. Insilico Medicine and Mellon’s company also formed a joint venture called Juvenescence AI to investigate the therapeutic properties of specific compounds. Mellon is particularly optimistic that this venture can develop a “senolytic” drug that helps the body clear out cells that have stopped dividing and can damage other cells.
Using Nanoscale Robots to Fight Aging and Disease
At least in the developed world, cancer, heart diseases, and neurodegenerative diseases are among the greatest causes of mortality. One emerging and very promising way to prevent or cure these diseases is through bio-nanotechnology.
Nanotechnology is the design, synthesis and application of materials or devices that are on the nanometer scale (one billionth of a meter). Due to the small scale of these devices, they can have many beneficial applications, both in industry and medicine. The use of nanodevices in medicine is called nanomedicine. Here, we will look at some applications of nanomedicine in curing or preventing the diseases that are most likely to kill us.
10 Charts That Will Change Your Perspective On Artificial Intelligence’s Growth
- There has been a 14X increase in the number of active AI startups since 2000. Crunchbase, VentureSource, and Sand Hill Econometrics were also used for completing this analysis with AI startups in Crunchbase cross-referenced to venture-backed companies in the VentureSource database. Any venture-backed companies from the Crunchbase list that were identified in the VentureSource database were included.
- The share of jobs requiring AI skills has grown 4.5X since 2013., The growth of the share of US jobs requiring AI skills on the Indeed.com platform was calculated by first identifying AI-related jobs using titles and keywords in descriptions. Job growth is a calculated as a multiple of the share of jobs on the Indeed platform that required AI skills in the U.S. starting in January 2013. The study also calculated the growth of the share of jobs requiring AI skills on the Indeed.com platform, by country. Despite the rapid growth of the Canada and UK. AI job markets, Indeed.com reports they are respectively still 5% and 27% of the absolute size of the US AI job market.
- Machine Learning, Deep Learning and Natural Language Processing (NLP) are the three most in-demand skills on Monster.com. Just two years ago NLP had been predicted to be the most in-demand skill for application developers creating new AI apps. In addition to skills creating AI apps, machine learning techniques, Python, Java, C++, experience with open source development environments, Spark, MATLAB, and Hadoop are the most in-demand skills. Based on an analysis of Monster.com entries as of today, the median salary is $127,000 in the U.S. for Data Scientists, Senior Data Scientists, Artificial Intelligence Consultants and Machine Learning Managers.
- Error rates for image labeling have fallen from 28.5% to below 2.5% since 2010. AI’s inflection point for Object Detection task of the Large Scale Visual Recognition Challenge (LSVRC) Competition occurred in 2014. On this specific test, AI is now more accurate than human These findings are from the competition data from the leaderboards for each LSVRC competition hosted on the ImageNet website.
- Internationally, robot imports have risen from around 100,000 in 2000 to around 250,000 in 2015. The data displayed is the number of industrial robots imported each year into North America and Internationally. Industrial robots are defined by the ISO 8373:2012 standard. International Data Corporation (IDC) expects robotics spending to accelerate over the five-year forecast period, reaching $230.7B in 2021, attaining a Compound Annual Growth Rate (CAGR) of 22.8%.
- Global revenues from AI for enterprise applications is projected to grow from $1.62B in 2018 to $31.2B in 2025 attaining a 52.59% CAGR in the forecast period. Image recognition and tagging, patient data processing, localization and mapping, predictive maintenance, use of algorithms and machine learning to predict and thwart security threats, intelligent recruitment, and HR systems are a few of the many enterprise application use cases predicted to fuel the projected rapid growth of AI in the enterprise. Source: Statista.
- 84% of enterprises believe investing in AI will lead to greater competitive advantages. 75% believe that AI will open up new businesses while also providing competitors new ways to gain access to their markets. 63% believe the pressure to reduce costs will require the use of AI. Source: Statista.
- 87% of current AI adopters said they were using or considering using AI for sales forecasting and for improving e-mail marketing. 61% of all respondents said that they currently used or were planning to use AI for sales forecasting. The following graphic compares adoption rates of current AI adopters versus all respondents. Source: Statista.
