3 Myths About Machine Learning in Health Care

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Machine learning will dramatically improve health care. There are already a myriad impactful ML health care applications from imaging to predicting readmissions to the back office. But there are also high-profile, expensive efforts that have not achieved their goals. In our collective roles as the CEO of a care delivery analytics business, tech-driven clinicians, and the leader of tech innovation at a major health system, we have developed and used dozens of ML applications. Many of these have succeeded, but others have not.


Incident Response Machine Learning with Chris Riley - Software Engineering Daily

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Software bugs cause unexpected problems at every company. A website goes down in the middle of the night, and the outage triggers a phone call to an engineer who has to wake up and fix the problem. Other problems can be significantly larger. When a major problem occurs, it can cause millions of dollars in losses and requires hours of work to fix. When software unexpectedly breaks, it is called an incident.


Be more efficient to produce ML models with mlflow

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Hello, In this article I am going to make an experiment on a tool called mlflow that come out last year to help data scientist to better manage their machine learning model. The idea of this article is not to build the perfect model for the use case where I am going to build a machine learning model, but more to dive on the functionalities of mlflow and see how it can be integrated in a ML pipeline to bring efficiency in the daily basis for a data scientist/ machine learning engineer. There are three pillars around mlflow (). Their documentation is really great and they have a nice tutorial to explain the component of mlflow. For this article I am going to focus my test on the Tracking and Models parts of mlflow because I will be honest with you I didn't see the point on the Project part (looks like a conda export and a config file to run python script in a specific order) but I am sure it can help some people on the reproductive aspect of an ml pipeline.


The Invasion of AI/ML into Android Smartphones RoboticsTomorrow

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The migration to utilizing AI and ML in mobile systems locally'in memory' has happened very fast within a few short years. We've been reading about the tremendous developments in AI and ML achieved by Apple the latest iPhone 11 and Tesla in their new neural network chip to help achieve autonomous driving in their cars within the next year or two. Now, Gyrfalcon Technology Inc. (GTI) has developed an AI Neural Accelerator that enables smartphones like the LG Q70 to benefit from high performance & low power all at a much lower price point. We expect to see hundreds of products using GTI AI Accelerator chips before too long. Artificial Intelligence (AI) and Machine Learning (ML) have been around a long time but are gaining new popularity due to the ability to get these technologies to do some amazing things like beat anyone at chess, recognize someone walking in public from millions of stored faces and other problems which lend themselves to problems that require a lot of parallel processing.


Problems of Lack of Transparency Pervade Issues of Algorithms in Artificial Intelligence

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WASHINGTON, November 12, 2019 - The advent of artificial intelligence raises the concern of whether online algorithms harm or help user bias, experts said at a Tuesday Brookings panel. The remarkable lack of transparency is evident in how companies analyze algorithms, said Solon Barocas, information science professor at Cornell University. Before technology became ubiquitous, it was easier for people to recognized blatant discrimination from companies. Now, he said, it's more difficult to detect these signs from an online platform. The reasons creditors provide to customers for adverse decisions, Barocas said, are not entirely useful.


Boston Dynamics CEO on the company's top 3 robots, AI, and viral videos

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And we focus really on the athletic part of it. I think, though, that if you do a good job on the athletic part, which is also kind of the low-level part, you can make it easier for high-level AI to interact with you." In other words, it's much easier to direct a robot to take care of a task for you if you've already taught the robot how to stand, walk, navigate, and so on.


A List of Artificial Intelligence Tools for Industry Specific

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Here's a look at industry specific companies that utilise various forms of artificial intelligence to solve some really interesting and particular problems for different markets. If you want to be included in any of the list don't forget to comment below. If you use Apple News or similar simple visit the site on a web browser to make comments. Imagia -- helps detect changes in cancer early Kuznech -- computer vision products range Lunit Inc. -- a range of medical imaging software Zebra Medical Vision -- medical imaging to help physicians and practitioners Aerial Achron -- automated UAV operations Airware -- drones for industrial purposes Alive.ai Developers, Studios and Consultants (only a few listed) Aitia Amplify Applied AI Blindspot Solutions Cogent Crossing Minds DSP Expert Systems Explosion Minds.ai


Business investment in AI and IoT not to increase in 2020

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Emerging tech such as IoT and AI is the second lowest priority for businesses next year for the third year running, second only to print services. That is outlook from a survey conducted by business tech provider Softcat, which asked its 1,600 customers across 18 different industries about their intentions for tech spending in 2020. Among those industries, real estate, private health and social work, and energy and utilities ranked big data, IoT and AI seventh and eighth priority respectively – the highest ranking by those questioned. The survey also reports that 56 percent of industries rank end user computing and mobility, the technology which allows for remote working, as their second biggest technology priority. The construction, education and healthcare industries ranked this as their number one priority, ahead of cyber security investment.


Darktrace wins prestigious Artificial Intelligence Award

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The Lloyds Bank National Business Awards is the flagship awards programme that recognises and rewards excellence across all sectors in the UK, celebrating businesses that combine creativity and innovation with results, and recognize companies that set new standards of excellence within their industries.


Microsoft is losing a key AI exec during a crucial moment that could shape the future of the company

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Microsoft is losing a key executive who helped the Redmond-based company turn artificial intelligence research into products just as its AI business is getting off the ground. Harry Shum, who runs Microsoft's AI and Research group, is leaving in February after 23 years at Microsoft. He has already shifted his group and responsibilities to Microsoft Chief Technology Officer Kevin Scott, which include overseeing the company's AI strategy, research and development on infrastructure, services, and apps, and AI-focused product groups including Bing. The news was first reported by ZDNet's Mary Jo Foley, and confirmed by Microsoft to Business Insider. Shum's departure comes at a time when Microsoft is making big investments in AI.