IBM Announces Advances in Watson’s Cognitive Computing Capabilities

August 28, 2014

NEW YORK, N.Y., Aug. 28 — IBM today announced significant advances in Watson‘s cognitive computing capabilities that are enabling researchers to accelerate the pace of scientific breakthroughs by discovering previously unknown connections in Big Data.

Available now as a cloud service, IBM’s Watson Discovery Advisor is designed to scale and accelerate discoveries by research teams. It reduces the time needed to test hypotheses and formulate conclusions that can advance their work — from months to days and days to just hours — bringing new levels of speed and precision to research and development.

Building on Watson’s ability to understand nuances in natural language, Watson Discovery Advisor can understand the language of science, such as how chemical compounds interact, making it a uniquely powerful tool for researchers in life sciences and other industries.  

Researchers and scientists from leading academic, pharmaceutical and other commercial research centers have begun deploying IBM’s new Watson Discovery Advisor to rapidly analyze and test hypotheses using data in millions of scientific papers available in public databases. A new scientific research paper is published nearly every 30 seconds, which equals more than a million annually (Source: CiteSeerx). According to the National Institutes of Health, a typical researcher reads about 23 scientific papers per month, which translates to nearly 300 per year, making it humanly impossible to keep up with the ever-growing body of scientific material available.

In 2013, the top 1,000 research and development companies spent more than $600 billion annually on research alone (Source: Strategy&). Progress can be slow, taking an average of 10 to 15 years for a promising pharmaceutical treatment to progress from the initial research stage into practice (Source: Pharmaceutical Research and Manufacturers of America). Using Watson Discovery Advisor, researchers can uncover new relationships and recognize unexpected patterns among data that have the potential to significantly improve and accelerate the discovery process in research and science.

“We’re entering an extraordinary age of data-driven discovery,” said Mike Rhodin, senior vice president, IBM Watson Group. “Today’s announcement is a natural extension of Watson’s cognitive computing capability. We’re empowering researchers with a powerful tool which will help increase the impact of investments organizations make in R&D, leading to significant breakthroughs.”

Leading life sciences organizations are deploying Watson Discovery Advisor to advance discoveries in ongoing research projects, including Baylor College of Medicine, Johnson & Johnson and The New York Genome Center.

  • In a retrospective, peer reviewed study released this week by Baylor College of Medicine and IBM, scientists demonstrated a possible new path for generating scientific questions that may be helpful in the long term development of new, effective treatments for disease. In a matter of weeks, biologists and data scientists using the Baylor Knowledge Integration Toolkit (KnIT), based on Watson technology, accurately identified proteins that modify p53, an important protein related to many cancers, which can eventually lead to better efficacy of drugs and other treatments. A feat that would have taken researchers years to accomplish without Watson’s cognitive capabilities, Watson analyzed 70,000 scientific articles on p53 to predict proteins that turn on or off p53’s activity. This automated analysis led the Baylor cancer researchers to identify six potential proteins to target for new research. These results are notable, considering that over the last 30 years, scientists averaged one similar target protein discovery per year. 

“On average, a scientist might read between one and five research papers on a good day,” said Dr. Olivier Lichtarge, the principal investigator and professor of molecular and human genetics, biochemistry and molecular biology at Baylor College of Medicine. “To put this in perspective with p53, there are over 70,000 papers published on this protein. Even if I’m reading five papers a day, it could take me nearly 38 years to completely understand all of the research already available today on this protein. Watson has demonstrated the potential to accelerate the rate and the quality of breakthrough discoveries. “

  • Johnson & Johnson is collaborating with the IBM Watson Discovery Advisor team to teach Watson to read and understand scientific papers that detail clinical trial outcomes used to develop and evaluate medications and other treatments. This collaboration hopes to accelerate comparative effectiveness studies of drugs, which help doctors match a drug with the right set of patients to maximize effectiveness and minimize side effects. Typically, comparative effectiveness studies are done manually, requiring three people to spend an average of 10 months (2.5 man-years) just to collect the data and prepare them for use before they are able to start analyzing, generating and validating a hypothesis. In this research study, the team hopes to teach Watson to quickly synthesize the information directly from the medical literature, allowing researchers to start asking questions about the data immediately to determine the effectiveness of a treatment compared to other medications, as well as its side effects. 
  • Sanofi is exploring how  working with Watson can speed up the discovery of alternate indications for existing drugs (drug re-purposing). Watson is able to understand and extract key information by reading millions of pages of scientific literature and then visualizes relationships between drugs and other potential diseases they could target while providing supporting evidence each step of the way. Drug Safety and Toxicity is a major driver of the high failure rate in clinical development /  trials.  Sanofi is exploring how Watson’s ability to understand, extract and organize toxicological information can enable researchers to make better informed decisions with respect to candidate progression
  • IBM Watson will be supporting the analysis in New York Genome Center’s clinical study to advance genomic medicine. The clinical study will initially focus on clinical application of genomics to help oncologists deliver DNA-based treatment for glioblastoma, an aggressive form of brain cancer that kills more than 13,000 Americans each year. Despite tremendous discoveries into the genetic drivers of diseases like cancer over the past decade, big data makes it difficult to translate DNA data into life-saving treatments. Based on results from the clinical study, IBM Watson could soon help scale up the availability of personalized treatment options.

Industry Implications 

Discovering something new is applicable to many domains such as medicine, law, finance, etc., that all require deep insight into a large body of information and protocols. Cognitive computing will allow human experts to interact with large bodies of data and research and the knowledge and insight of many other experts in their field. For example, Watson could be used to:

  • Accelerate a medical researcher’s ability to develop life-saving treatments for diseases by synthesizing evidence and removing reliance on serendipity
  • Enhance a financial analyst’s ability to provide proactive advice to clients
  • Improve a lawyer’s merger and acquisition strategy with faster, more comprehensive due diligence and document analysis
  • Accelerate a government analyst’s insight into security, intelligence, border protection and law enforcement and guidance, etc.
  • Create new food recipes. Chefs can use Watson to augment their creativity and expertise and help them discover recipes, learning about the language of cooking and food by reading recipes, statistical, molecular and food pairing theories, hedonic chemistry, as well as regional and cultural knowledge

Source: IBM

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industy updates delivered to you every week!

Trinity Supercomputer’s Haswell and KNL Partitions Are Merged

July 19, 2017

Trinity supercomputer’s two partitions – one based on Intel Xeon Haswell processors and the other on Xeon Phi Knights Landing – have been fully integrated are now available for use on classified work in the Nationa Read more…

By HPCwire Staff

Fujitsu Continues HPC, AI Push

July 19, 2017

Summer is well under way, but the so-called summertime slowdown, linked with hot temperatures and longer vacations, does not seem to have impacted Fujitsu's output. The Japanese multinational has made a raft of HPC and A Read more…

By Tiffany Trader

Researchers Use DNA to Store and Retrieve Digital Movie

July 18, 2017

From abacus to pencil and paper to semiconductor chips, the technology of computing has always been an ever-changing target. The human brain is probably the computer we use most (hopefully) and understand least. This mon Read more…

By John Russell

The Exascale FY18 Budget – The Next Step

July 17, 2017

On July 12, 2017, the U.S. federal budget for its Exascale Computing Initiative (ECI) took its next step forward. On that day, the full Appropriations Committee of the House of Representatives voted to accept the recomme Read more…

By Alex R. Larzelere

HPE Extreme Performance Solutions

HPE Servers Deliver High Performance Remote Visualization

Whether generating seismic simulations, locating new productive oil reservoirs, or constructing complex models of the earth’s subsurface, energy, oil, and gas (EO&G) is a highly data-driven industry. Read more…

Summer Reading: IEEE Spectrum’s Chip Hall of Fame

July 17, 2017

Take a trip down memory lane – the Mostek MK4096 4-kilobit DRAM, for instance. Perhaps processors are more to your liking. Remember the Sh-Boom processor (1988), created by Russell Fish and Chuck Moore, and named after Read more…

By John Russell

Women in HPC Luncheon Shines Light on Female-Friendly Hiring Practices

July 13, 2017

The second annual Women in HPC luncheon was held on June 20, 2017, during the International Supercomputing Conference in Frankfurt, Germany. The luncheon provides participants the opportunity to network with industry lea Read more…

By Tiffany Trader

Satellite Advances, NSF Computation Power Rapid Mapping of Earth’s Surface

July 13, 2017

New satellite technologies have completely changed the game in mapping and geographical data gathering, reducing costs and placing a new emphasis on time series and timeliness in general, according to Paul Morin, directo Read more…

By Ken Chiacchia and Tiffany Jolley

Intel Skylake: Xeon Goes from Chip to Platform

July 13, 2017

With yesterday’s New York unveiling of the new “Skylake” Xeon Scalable processors, Intel made multiple runs at multiple competitive threats and strategic markets. Skylake will carry Intel's flag in the fight for le Read more…

By Doug Black

Fujitsu Continues HPC, AI Push

July 19, 2017

Summer is well under way, but the so-called summertime slowdown, linked with hot temperatures and longer vacations, does not seem to have impacted Fujitsu's out Read more…

By Tiffany Trader

Researchers Use DNA to Store and Retrieve Digital Movie

July 18, 2017

From abacus to pencil and paper to semiconductor chips, the technology of computing has always been an ever-changing target. The human brain is probably the com Read more…

By John Russell

The Exascale FY18 Budget – The Next Step

July 17, 2017

On July 12, 2017, the U.S. federal budget for its Exascale Computing Initiative (ECI) took its next step forward. On that day, the full Appropriations Committee Read more…

By Alex R. Larzelere

Women in HPC Luncheon Shines Light on Female-Friendly Hiring Practices

July 13, 2017

The second annual Women in HPC luncheon was held on June 20, 2017, during the International Supercomputing Conference in Frankfurt, Germany. The luncheon provid Read more…

By Tiffany Trader

Satellite Advances, NSF Computation Power Rapid Mapping of Earth’s Surface

July 13, 2017

New satellite technologies have completely changed the game in mapping and geographical data gathering, reducing costs and placing a new emphasis on time series Read more…

By Ken Chiacchia and Tiffany Jolley

Intel Skylake: Xeon Goes from Chip to Platform

July 13, 2017

With yesterday’s New York unveiling of the new “Skylake” Xeon Scalable processors, Intel made multiple runs at multiple competitive threats and strategic Read more…

By Doug Black

Perverse Incentives? How Economics (Mis-)shaped Academic Science

July 12, 2017

The unintended consequences of how we fund academic research—in the U.S. and elsewhere—are strangling innovation, putting universities into debt and creatin Read more…

By Ken Chiacchia, Senior Science Writer, Pittsburgh Supercomputing Center

Why Tech is Failing at Diversity and How It Can Succeed

July 11, 2017

The sectors that are supposed to be all about innovation and the future continue to fail spectacularly at gender equity and diversity. UK, US and Canada still haven’t managed to break the average 20 percent threshold for gender equity across STEM academic disciplines. Read more…

By Kelly Nolan

HPC Compiler Company PathScale Seeks Life Raft

March 23, 2017

HPCwire has learned that HPC compiler company PathScale has fallen on difficult times and is asking the community for help or actively seeking a buyer for its a Read more…

By Tiffany Trader

Quantum Bits: D-Wave and VW; Google Quantum Lab; IBM Expands Access

March 21, 2017

For a technology that’s usually characterized as far off and in a distant galaxy, quantum computing has been steadily picking up steam. Just how close real-wo Read more…

By John Russell

Google Pulls Back the Covers on Its First Machine Learning Chip

April 6, 2017

This week Google released a report detailing the design and performance characteristics of the Tensor Processing Unit (TPU), its custom ASIC for the inference Read more…

By Tiffany Trader

Nvidia Responds to Google TPU Benchmarking

April 10, 2017

Nvidia highlights strengths of its newest GPU silicon in response to Google's report on the performance and energy advantages of its custom tensor processor. Read more…

By Tiffany Trader

Trump Budget Targets NIH, DOE, and EPA; No Mention of NSF

March 16, 2017

President Trump’s proposed U.S. fiscal 2018 budget issued today sharply cuts science spending while bolstering military spending as he promised during the cam Read more…

By John Russell

CPU-based Visualization Positions for Exascale Supercomputing

March 16, 2017

In this contributed perspective piece, Intel’s Jim Jeffers makes the case that CPU-based visualization is now widely adopted and as such is no longer a contrarian view, but is rather an exascale requirement. Read more…

By Jim Jeffers, Principal Engineer and Engineering Leader, Intel

Nvidia’s Mammoth Volta GPU Aims High for AI, HPC

May 10, 2017

At Nvidia's GPU Technology Conference (GTC17) in San Jose, Calif., this morning, CEO Jensen Huang announced the company's much-anticipated Volta architecture a Read more…

By Tiffany Trader

Facebook Open Sources Caffe2; Nvidia, Intel Rush to Optimize

April 18, 2017

From its F8 developer conference in San Jose, Calif., today, Facebook announced Caffe2, a new open-source, cross-platform framework for deep learning. Caffe2 is the successor to Caffe, the deep learning framework developed by Berkeley AI Research and community contributors. Read more…

By Tiffany Trader

Leading Solution Providers

How ‘Knights Mill’ Gets Its Deep Learning Flops

June 22, 2017

Intel, the subject of much speculation regarding the delayed, rewritten or potentially canceled “Aurora” contract (the Argonne Lab part of the CORAL “ Read more…

By Tiffany Trader

MIT Mathematician Spins Up 220,000-Core Google Compute Cluster

April 21, 2017

On Thursday, Google announced that MIT math professor and computational number theorist Andrew V. Sutherland had set a record for the largest Google Compute Engine (GCE) job. Sutherland ran the massive mathematics workload on 220,000 GCE cores using preemptible virtual machine instances. Read more…

By Tiffany Trader

Reinders: “AVX-512 May Be a Hidden Gem” in Intel Xeon Scalable Processors

June 29, 2017

Imagine if we could use vector processing on something other than just floating point problems.  Today, GPUs and CPUs work tirelessly to accelerate algorithms Read more…

By James Reinders

Google Debuts TPU v2 and will Add to Google Cloud

May 25, 2017

Not long after stirring attention in the deep learning/AI community by revealing the details of its Tensor Processing Unit (TPU), Google last week announced the Read more…

By John Russell

Russian Researchers Claim First Quantum-Safe Blockchain

May 25, 2017

The Russian Quantum Center today announced it has overcome the threat of quantum cryptography by creating the first quantum-safe blockchain, securing cryptocurrencies like Bitcoin, along with classified government communications and other sensitive digital transfers. Read more…

By Doug Black

Groq This: New AI Chips to Give GPUs a Run for Deep Learning Money

April 24, 2017

CPUs and GPUs, move over. Thanks to recent revelations surrounding Google’s new Tensor Processing Unit (TPU), the computing world appears to be on the cusp of Read more…

By Alex Woodie

Top500 Results: Latest List Trends and What’s in Store

June 19, 2017

Greetings from Frankfurt and the 2017 International Supercomputing Conference where the latest Top500 list has just been revealed. Although there were no major Read more…

By Tiffany Trader

Six Exascale PathForward Vendors Selected; DoE Providing $258M

June 15, 2017

The much-anticipated PathForward awards for hardware R&D in support of the Exascale Computing Project were announced today with six vendors selected – AMD Read more…

By John Russell

  • arrow
  • Click Here for More Headlines
  • arrow
Share This