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Machine learning takes on synthetic biology: algorithms can bioengineer cells for you

#artificialintelligence

If you've eaten vegan burgers that taste like meat or used synthetic collagen in your beauty routine--both products that are "grown" in the lab--then you've benefited from synthetic biology. It's a field rife with potential, as it allows scientists to design biological systems to specification, such as engineering a microbe to produce a cancer-fighting agent. Yet conventional methods of bioengineering are slow and laborious, with trial and error being the main approach. Now scientists at the Department of Energy's Lawrence Berkeley National Laboratory (Berkeley Lab) have developed a new tool that adapts machine learning algorithms to the needs of synthetic biology to guide development systematically. The innovation means scientists will not have to spend years developing a meticulous understanding of each part of a cell and what it does in order to manipulate it; instead, with a limited set of training data, the algorithms are able to predict how changes in a cell's DNA or biochemistry will affect its behavior, then make recommendations for the next engineering cycle along with probabilistic predictions for attaining the desired goal.


Artificial Intelligence Solutions for Banking

#artificialintelligence

Though banks don't create AI strategies, they are increasingly using artificial intelligence and machine learning in their day-to-day business. We frequently work with them on ideation workshops, PoC, and solution implementation. Santander Consumer Bank, for example, is running workshops and researching how to use machine learning to boost the sustainability of loan portfolios. Besides credit risk modeling, there is already an impressive range of use cases for AI in banking. It covers everything, from customer service to back-office operations.


AI's Latest Breakthrough Will Transform Learning--Here Are 5 Ways

#artificialintelligence

The Fourth Industrial Revolution just took a huge step forward, thanks to a breakthrough artificial intelligence (AI) model that can learn virtually anything about the world -- and produce the content to tell us about it. The AI program is GPT-3 by OpenAI, which started out as a language model to predict the next word in a sentence and has vastly exceeded that capability. Now, drawing from voluminous data -- essentially all of Wikipedia, links from Reddit, and other Internet content -- GPT-3 has shown it can also compose text that is virtually indistinguishable from human-generated content. Asger Alstrup Palm, Area9's chief technology officer, explained that GPT-3 was tasked with testing the "scaling hypothesis" -- to see if a bigger model with ever-increasing amounts of information would lead to better performance. Although it's too early to call the scaling hypothesis proven, there are some strong indications that this is, indeed, the case. Further validating the potential of GPT-3, Microsoft recently announced it will exclusively license the model from OpenAI, with the intention of developing and delivering AI solutions for customers and creating new solutions using natural language generation.


A short guide for medical professionals in the era of artificial intelligence

#artificialintelligence

Artificial intelligence (A.I.) is expected to significantly influence the practice of medicine and the delivery of healthcare in the near future. While there are only a handful of practical examples for its medical use with enough evidence, hype and attention around the topic are significant. There are so many papers, conference talks, misleading news headlines and study interpretations that a short and visual guide any medical professional can refer back to in their professional life might be useful. For this, it is critical that physicians understand the basics of the technology so they can see beyond the hype, evaluate A.I.-based studies and clinical validation; as well as acknowledge the limitations and opportunities of A.I. This paper aims to serve as a short, visual and digestible repository of information and details every physician might need to know in the age of A.I. We describe the simple definition of A.I., its levels, its methods, the differences between the methods with medical examples, the potential benefits, dangers, challenges of A.I., as well as attempt to provide a futuristic vision about using it in an everyday medical practice.


Art with AI: Turning photographs into artwork with Neural Style Transfer

#artificialintelligence

Please Note: I reserve the rights of all the media used in this blog -- photographs, animations, videos, etc. they are my work (except the 7 mentioned artworks by artists which were used as style images). GIFs might take a while to load, please be patient. If that is the case please open in browser instead. The world today doesn't make sense, so why should I paint pictures that do? -- Pablo Picasso Here are the results, some combinations produced astounding artwork. Here's an image of a bride & graffiti, combining them results in an output similar to doodle painting. Here, you can see the buildings being popped up in the background.


Dubai school ties up with MIT for first-of-its-kind artificial intelligence curriculum

#artificialintelligence

Under the project, students will learn a customised version -- unique to the project -- of the popular programming language Scratch. They will also use MIT App Inventor that runs on Android devices and work on developing a robot kit in conjunction with Chromebooks. Students will study CT (computational thinking), the cornerstone computer science discipline that renders complex problems simple so that humans and computers can understand the possible solutions. This includes'pattern recognition', looking for similarities among data, and writing algorithms -- a step-by-step guide to solving a problem or task. Pupils will also learn skills such as'debugging' to identify and remove software or hardware errors and practises like'tinkering' to innovate and build on experimental models or prototypes.


Always Home Cam: Amazon's robot drone flying inside our homes seems like a bad idea

ZDNet

I actually had to double-check my calendar to make sure today wasn't April Fool's. Because watching the intro video of an indoor surveillance drone operated by Amazon seemed like just the sort of geeky joke you'd expect on April 1. But it isn't April Fools, and besides, Google has always been the one with the twisted sense of humor. Amazon has always been the one with the twisted sense of world domination. This was a serious press briefing.


The best wireless workout headphones

Engadget

As some of you might know, I'm a runner. On occasion I review sports watches, and outside of work I'm a certified marathon coach. So when it became clear Engadget wanted to round up the best wireless workout headphones, I raised my hand. And the timing feels particularly appropriate. Until now I was still using wired buds (old habits die hard), and it happened that every pair I owned was on the fritz.


How to bring Zoom to your TV (coming soon) with Alexa

USATODAY - Tech Top Stories

If you're also tired of taking daily Zoom calls on your laptop, maybe you'd prefer to just turn on the TV, lay back, and learn or conduct business from the couch. Earlier this week, we wrote about a new video device for Microsoft Teams, but it's really large, at 85 inches, and really costly, at $21,199. Amazon is introducing a less pricey option later this year. "I just believe that your big, beautiful TV is a great place for communications and we're going to continue to lean in to make that a better experience well," said Marc Whitten, vice president of Amazon Entertainment Devices and Services. To drive the new device,you'll need the Fire TV Cube, a $119 accessory that's different from the Fire TV streaming stick units.


Breakthrough in safety-critical machine learning could be just the beginning

#artificialintelligence

Safety is the central focus on driverless vehicle systems development. Artificial intelligence (AI) is coming at us fast. It's being used in the apps and services we plug into daily without us really noticing, whether it's a personalized ad on Facebook, or Google recommending how you sign off your email. If these applications fail, it may result in some irritation to the user in the worst case. But we are increasingly entrusting AI and machine learning to safety-critical applications, where system failure results in a lot more than a slight UX issue.