Who is ibm watson

Watson was initially built to answer questions on Jeopardy, an American quiz show. Watson has a Power7 processor. It has 16 terabytes of RAM and uses a 3. It has the potential to process GB of information per second, equal to a million books. As the device performs text mining and complex analytics on voluminous amounts of unstructured data, it can support a search engine or an expert system with capabilities far superior to any previously existing.

Watson leverages the power of machine learning to answer questions. It allows users to learn more with fewer data. With IBM Watson , users can protect their insights as it gives them control over what is important to them.

Everyone likes ambition, everyone likes moon shots, but nobody wants to climb into a rocket that doesn't work. IBM began its effort to bring Watson into the health care industry in Since then, the company has made nearly 50 announcements about partnerships that were intended to develop new AI-enabled tools for medicine. Some collaborations worked on tools for doctors and institutions; some worked on consumer apps.

While many of these alliances have not yet led to commercial products, IBM says the research efforts have been valuable, and that many relationships are ongoing. Here's a representative sample of projects. She holds a master's degree in journalism from Columbia University.

Craig S. China has taken another step toward semiconductor independence with Alibaba announcing the design of a 5-nanometer technology server chip that is based on Arm Ltd. But, impressive as that feat is, an even more significant chip design development by the Chinese tech giant may be making available the source code to a RISC-V CPU core its own engineers designed.

This means other companies can use it in their own processor designs—and escape architecture license fees. The company made both announcements at its annual cloud convention in its home city of Hangzhou last month. The Chinese government is funding a lot of startups that are designing a variety of chips. The number of newly registered Chinese chip-related companies more than tripled in the first five months of from the same period a year ago.

And the biggest Chinese technology companies like Alibaba, Baidu, and Huawei are developing their own chips rather than banking on those from Intel, Nvidia, and other United States-based companies. China is intent on developing semiconductor independence, both in design and manufacture of state-of-the-art chips. The urgency for doing so has been helped along by U. The sanctions extend to any Huawei suppliers that use U. The United States, alarmed at China's campaign to bring Taiwan under its control, has also begun an ambitious program to 'reshore' its semiconductor manufacturing after allowing much of it to migrate to Taiwan.

Around 80 percent of the world's semiconductor production capacity is in Asia, and nearly all the most advanced logic chip production is in Taiwan. No Chinese semiconductor foundry has yet achieved the 5-nanometer processing needed to make Alibaba's new ARM-based chip, so it is still beholden to Taiwan for manufacturing. But the implications of Alibaba's general choice of Arm and RISC-V instruction set architectures is perhaps more consequential for the long term.

An instruction set architecture, or ISA, is the language in which software talks to hardware, and thus determines the kind of software that can run on a particular chip. Most servers use CPUs based on Intel's x86 instruction set architecture. But UK-based Arm, which licenses its instruction set architecture to chip designers, has been gaining a foothold in this market. RISC-V, which refers to the fifth generation of an open-source reduced instruction set computer architecture created by U.

This past June, China hosted the fourth annual RISC-V summit, bringing together industry, academia, and government to talk about the future of the architecture. In the wake of the U. Unable to buy Intel chips because of the sanctions, Huawei most recently sold its x86 server unit to a company owned by China's Henan province. From the beginning, the company indicated that it intended to open the CPU's source code—the hardware description language that describes the structure and behavior of the CPU core's electronic circuits.

It has now done so… with little fanfare. Its Yitian server system on a chip SoC , manufactured by Taiwan's TSMC, will have a total of Arm-based cores, with 60 billion integrated transistors and a top clock speed of 3. Alibaba said it is the first server processor compatible with the latest Armv9 architecture. Alibaba said the SoC achieved a score of in SPECint a standard benchmark for measuring CPU integer processing power , surpassing that of the current state-of-the-art Arm server processor based on Armv8 by 20 percent in performance and 50 percent in energy efficiency.

The company also announced the development of proprietary servers, under the brand name Panjiu , developed for the next-generation of cloud-native infrastructure. By separating computing from storage, the servers are optimized for both general-purpose and specialized AI computing, as well as high-performance storage. The company vowed to provide more services and support for RISC-V development tools, software development kits, and customized cores in the future.

Consultant Gwennap suggests that Alibaba's Arm and RISC-V efforts are experiments more than commercial endeavors, noting that Alibaba is still using x86 Intel chips for the vast majority of its internal use.

Alibaba's new Arm-based server chip will be used in Alibaba datacenters to provide cloud services to customers..

The company will continue to offer Intel-based services, so it's up to customers to choose Arm over xbased chips. When Amazon did something similar a few years ago, there was little uptake for the Arm-based chips. But true semiconductor independence will require China to develop its own extreme ultraviolet lithography machines , required to etch microscopic circuits on silicon. SMIC , China's main chip foundry, can't provide anything smaller than 14 nm.

SMIC claims to have mastered the 3nm chip process in the lab and is trying to buy the EUV lithography machines necessary for production from ASML, the Dutch company that currently has a monopoly on the critical equipment. But the United States is intent on blocking the sale. But getting that technology out of the lab and into a machine remains many years away. Japanese startup working towards autonomous robots that can do useful work inside and outside the space station.

Late last year, Japanese robotics startup GITAI sent their S1 robotic arm up to the International Space Station as part of a commercial airlock extension module to test out some useful space-based autonomy. Everything moves pretty slowly on the ISS, so it wasn't until last month that NASA astronauts installed the S1 arm and GITAI was able to put the system through its paces —or rather, sit in comfy chairs on Earth and watch the arm do most of its tasks by itself, because that's the dream, right?

So what's next for commercial autonomous robotics in space? One of the advantages of working in space is that it's a highly structured environment. Microgravity can be somewhat unpredictable, but you have a very good idea of the characteristics of objects and even of lighting because everything that's up there is excessively well defined.

So, stuff like using a two-finger gripper for relatively high precision tasks is totally possible, because the variation that the system has to deal with is low. Of course, things can always go wrong, so GITAI also tested teleop procedures from Houston to make sure that having humans in the loop was also an effective way of completing tasks.

Since full autonomy is vastly more difficult than almost full autonomy, occasional teleop is probably going to be critical for space robots of all kinds. GITAI will apply the general-purpose autonomous space robotics technology, know-how, and experience acquired through this tech demo to develop extra-vehicular robotics EVR that can execute docking, repair, and maintenance tasks for On-Orbit Servicing OOS or conduct various activities for lunar exploration and lunar base construction.

I'm sure you did many tests with the system on the ground before sending it to the ISS. How was operating the robot on the ISS different from the testing you had done on Earth? The biggest difference between experiments on the ground and on the ISS is the microgravity environment, but it was not that difficult to cope with. However, experiments on the ISS, which is an unknown environment that we have never been to before, are subject to a variety of unexpected situations that were extremely difficult to deal with, for example an unexpected communication breakdown occurred due to a failed thruster firing experiment on the Russian module.

However, we were able to solve all the problems because the development team had carefully prepared for the irregularities in advance. It looked like the robot was performing many tasks using equipment designed for humans.

Do you think it would be better to design things like screws and control panels to make them easier for robots to see and operate? Yes, I think so. Unlike the ISS that was built in the past, it is expected that humans and robots will cooperate to work together in the lunar orbiting space station Gateway and the lunar base that will be built in the future.

Therefore, it is necessary to devise and implement an interface that is easy to use for both humans and robots. We are planning to conduct an on-orbit extra-vehicular demonstration in and a lunar demonstration in We are also working on space robot development projects for several customers for which we have already received orders.

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Biomedical Topic Type Feature After its triumph on Jeopardy! Doctors are still waiting. Since , IBM Watson has announced a multitude of projects in health care. How have they fared? Robotic Surgery Image Analysis Genetic Analysis Pathology Currently used only for routine steps in simple procedures like laser eye surgery and hair transplants.

Experts are just beginning to use automated systems to help them examine X-rays, retina scans, and other images. Since then, IBM has widely deployed Watson in many industry verticals and areas of application, and it has become the gold standard for purposeful analytics processing.

Read this primer on IBM Watson to understand what it is and how it is being used. We'll update the guide periodically with the latest news about IBM Watson. IBM Watson is a data analytics processor that uses natural language processing, a technology that analyzes speech for meaning and syntax and translates this into actionable answers. The goal of the project was to develop a natural language-responsive system that could interpret questions asked in a human language and then analyze vast amounts of data and return answers that it would take human researchers days, weeks, or even months to derive.

The Jeopardy! The application performed cost management analysis in the treatment of lung cancer. Today, IBM Watson is used in a multitude of industry sectors with specialized information needs, including veterinary science, environmental and geotechnical engineering, education, government, food and beverage, legal, and music and entertainment.

What distinguishes IBM Watson from other analytics software is its direct relevance to business problem solving. Watson has the ability to rapidly analyze gargantuan repositories of data, documents, and other artifacts; it also comes with a level of human speech pattern recognition and language understanding that was elusive for many artificial intelligence applications in the past. IBM Watson uses cognitive learning practices that combine the data analytics and statistical reasoning of machines with uniquely human qualities, such as self-directed goals, common sense, and ethical values.

As a top layer to all of this, IBM has packaged various versions of Watson to address the specific business concerns and questions of different industry verticals. Watson processes unstructured text and documentation by "learning" a subject by pairing questions and answers after the user loads all related materials e.

The platform is capable of processing millions of documents, and reading million pages of data per second. IBM Watson also processes natural language, which can help businesses be more efficient. For example, an insurance company or a healthcare company can use Watson to review medical reports in order to isolate key medical terms; or a physician might use Watson to pore through millions of pages of clinical research in an attempt to isolate a medical condition, and arrive at a diagnosis and treatment plan.