Turbotodd

Ruminations on IT, the digital media, and some golf thrown in for good measure.

Archive for the ‘artificial intelligence’ Category

IBM and MIT to Pursue Joint Research in Artificial Intelligence

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IBM and MIT today announced that IBM plans to make a 10-year, $240 million investment to create the MIT–IBM Watson AI Lab in partnership with MIT. The lab will carry out fundamental artificial intelligence (AI) research and seek to propel scientific breakthroughs that unlock the potential of AI.

The collaboration aims to advance AI hardware, software and algorithms related to deep learning and other areas, increase AI’s impact on industries, such as health care and cybersecurity, and explore the economic and ethical implications of AI on society. IBM’s $240 million investment in the lab will support research by IBM and MIT scientists.

The new lab will be one of the largest long-term university-industry AI collaborations to date, mobilizing the talent of more than 100 AI scientists, professors, and students to pursue joint research at IBM’s Research Lab in Cambridge — co-located with the IBM Watson Health and IBM Security headquarters in Kendall Square, in Cambridge, Massachusetts — and on the neighboring MIT campus.

The lab will be co-chaired by IBM Research VP of AI and IBM Q, Dario Gil, and Anantha P. Chandrakasan, dean of MIT’s School of Engineering. IBM and MIT plan to issue a call for proposals to MIT researchers and IBM scientists to submit their ideas for joint research to push the boundaries in AI science and technology in several areas, including:

  • AI algorithms: Developing advanced algorithms to expand capabilities in machine learning and reasoning. Researchers will create AI systems that move beyond specialized tasks to tackle more complex problems, and benefit from robust, continuous learning. Researchers will invent new algorithms that can not only leverage big data when available, but also learn from limited data to augment human intelligence.
  • Physics of AI: Investigating new AI hardware materials, devices, and architectures that will support future analog computational approaches to AI model training and deployment, as well as the intersection of quantum computing and machine learning. The latter involves using AI to help characterize and improve quantum devices, and also researching the use of quantum computing to optimize and speed up machine-learning algorithms and other AI applications.
  • Application of AI to industries: Given its location in IBM Watson Health and IBM Security headquarters and Kendall Square, a global hub of biomedical innovation, the lab will develop new applications of AI for professional use, including fields such as health care and cybersecurity. The collaboration will explore the use of AI in areas such as the security and privacy of medical data, personalization of healthcare, image analysis, and the optimum treatment paths for specific patients.
  • Advancing shared prosperity through AI: The MIT-IBM Watson AI Lab will explore how AI can deliver economic and societal benefits to a broader range of people, nations, and enterprises. The lab will study the economic implications of AI and investigate how AI can improve prosperity and help individuals achieve more in their lives.

In addition to IBM’s plan to produce innovations that advance the frontiers of AI, a distinct objective of the new lab is to encourage MIT faculty and students to launch companies that will focus on commercializing AI inventions and technologies that are developed at the lab. The lab’s scientists also will publish their work, contribute to the release of open source material, and foster an adherence to the ethical application of AI.

Both MIT and IBM have been pioneers in artificial intelligence research, and the new AI lab builds on a decades-long research relationship between the two. In 2016, IBM Research announced a multi-year collaboration with MIT’s Department of Brain and Cognitive Sciences to advance the scientific field of machine vision, a core aspect of artificial intelligence.

The collaboration has brought together leading brain, cognitive, and computer scientists to conduct research in the field of unsupervised machine understanding of audio-visual streams of data, using insights from next-generation models of the brain to inform advances in machine vision. In addition, IBM and the Broad Institute of MIT and Harvard have established a five-year, $50 million research collaboration on AI and Genomics.

For more information, visit MITIBMWatsonAILab.mit.edu.

Written by turbotodd

September 7, 2017 at 9:09 am

HSBC and IBM Develop Cognitive Intelligence Solution to Digitize Global Trade

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HSBC, the world’s leading trade finance bank, is working with IBM to develop a cognitive intelligence solution combining optical character recognition with advanced robotics to make global trade safer and more efficient for thousands of businesses.

HSBC’s Global Trade and Receivables Finance (GTRF) team facilitates over U.S. $500 billion of documentary trade for customers every year, and in doing so must manually review and process up to 100 million pages of documents, ranging from invoices to packing lists and insurance certificates.

The new solution uses IBM’s advanced analytics technology, including intelligent segmentation and text analytics, to identify, digitise and extract key data within these documents before feeding it into the bank’s transaction processing systems; boosting accuracy whilst freeing up staff for more value-adding activities.

“The average trade transaction requires 65 data fields to be extracted from 15 different documents, with 40 pages to be reviewed,” said Natalie Blyth, HSBC’s Global Head of GTRF. “By digitising this process we will make transactions quicker and safer for both buyers and suppliers, leading our industry forwards, and we will reduce compliance risks through an enhanced ability to manage huge volumes of data.”

“The problem is how to capture semi-structured documents with highly variant content through an analogue process, and no-one has the perfect answer,” said Roger Welch, Industry (Financial) Expert and Solution Architect for IBM Analytics ECM practice. “In our experience, no trade finance solution has come as far or done as much as this new solution.”

HSBC is currently using the technology to analyse English-language import and export bills in several markets in Asia, Europe, the Americas and the MENA region. The team aims to enhance the solution so it can read a wider range of documents and languages including French, Spanish and Chinese.

“We are continuously investing in technologies that will improve the way we work for the benefit of our customers and our people,” said Natalie Blyth. “HSBC wants to be the leading bank for innovation, and initiatives like this one are key to achieving our goal.”

You can learn more about IBM Watson Financial Services here.

Written by turbotodd

August 10, 2017 at 9:19 am

Codify Academy Users IBM Cloud, Watson to Design Cognitive Chatbot

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IBM recently announced that Codify Academy, a San Francisco-based developer education startup, tapped into IBM Cloud’s cognitive services to create an interactive cognitive chatbot, Bobbot, that is improving student experiences and increasing enrollment.

Using the IBM Watson Conversation Service, Bobbot fields questions from prospective and current students in natural language via the company’s website.

Since implementing the chatbot, Codify Academy has engaged thousands of potential leads through live conversation between the bot and site visitors, leading to a 10 percent increase in converting these visitors into students.

IBM Cloud with Watson provided Codify Academy with the speed and scale needed to immediately start building with cognitive intelligence. Bobbot can answer more than 200 common questions about enrollment, course and program details, tuition, and prerequisites, in turn enabling Codify Academy staff to focus on deeper, more meaningful exchanges.

For example, students can ask questions such as “What kind of job will I be able to find after I complete the program?” or “How do I apply, and what are tuition rates?”

“We saw a huge spike in interest from potential students in the early days of our company, which is a fortunate problem to have, but made us realize we needed to quickly build a solution to help us scale,” said Matt Brody at Codify Academy. “IBM Cloud gave us the infrastructure and access to cognitive services, including Watson, that we needed to quickly build and deploy an intelligent and intuitive bot – in turn helping us to field all inquiries and significantly increase enrollment.”

Codify Academy runs on the IBM Cloud platform, which has become one of the largest open, public cloud deployments in the world. It features more than 150 tools and services, spanning categories of cognitive intelligence, blockchain, security, Internet of Things, quantum computing and DevOps.

“We have designed our cloud platform to serve as the best possible engine for cognitive apps such as chatbots," said Adam Gunther, Director, IBM Cloud. "This enables companies to harness and fine tune incoming data quickly to create highly tailored user experiences.”

To learn more about Codify Academy, visit http://codifyacademy.com/.

Written by turbotodd

August 4, 2017 at 1:42 pm

Bot to Bot

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Facebook’s been in the news a fair amount this week.

Pivotal Research lowered its rating on Facebook to “sell” from “hold,” according to a report from CNBC, explaining it is “facing digital ad saturation risk as large companies are ‘scrutizing’ their marketing budgets.”

This despite the fact that Facebook has been one of the best-performing large-cap stocks in the market, growing nearly 50 percent year to date.

Earlier today, Fortune reported that Facebook is amping up its artificial intelligence capabilities, buying Ozlo, a small bot specialist based in Palo Alto.

Ozlo focuses on “conversational” bots that talk to users, and most of the company’s employees will join Facebook’s Messenger team.

But the story that really seemed to grab the Facebook headlines this week was the one that indicated two of its bots, instead of just talking to humans, were talking to one another and in a language that the chatbots “invented.”

Before you go all “Westworld” on me, let’s separate the fact from the fiction.

In an account from Karissa Bell at Mashable, Bell provided some much needed background to stifle the hype and get to the actual innovation. Bell wrote that “Facebook’s AI researchers published a paper back in June, detailing their efforts to teach chatbots to negotiate like humans. Their intention was to train the bots not just to imitate human interactions, but to actually act like humans.”

Which humans, we’re not yet sure of. The Mooch? Kim Kardashian? Kid Rock (Soon to be Senator Rock, to you!)

Unclear.

But Bell’s observation was that the narrative wasn’t just about the chats coming up with their own language, but instead this: That not only did the bots learn to act like humans, actual humans were apparently unable to discern the difference between bots and humans.

Where the bot chatter went off the rails was in their use of the English language, the grammar and syntax rules for which the bots were not instructed to use. Hence, some of the shortcut phrases like “I can can I I everything else.”

In the meantime, Elon Musk has cried AI Chicken Little once again, suggesting all this neural networking could be the end of humankind once and for all and that Zuck doesn’t “fully understand” the potential danger posed by AI.

The truth probably rests somewhere in the vast middle ground between the two, a truth I imagine the bots are having a good chuckle over as they create the new digital Esperanto they’ll need to take over the world.

Written by turbotodd

August 1, 2017 at 10:59 am

Back in a Flash

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Head ups. Adobe has announced it will stop updating and distributing Flash at the end of 2020.

You’ve been given ample warning.

TechCrunch is reporting that until then, Adobe will still partner with the likes of Apple, Mozilla, Microsoft and Google to offer security updates for Flash in their browsers and support new versions of them, but beyond that, it’s no frills Flash, all the time.

HTML5 has won the day.

***

U.S. President Donald Trump said yesterday in an interview that Apple CEO Tim Cook has committed to build three big manufacturing plants in the U.S., but didn’t elaborate on where those plants would be located or when they would be built.

Do these new Apple plants get build before the Wall on the U.S./Mexico border, or after?

Sorry, I NAFTA hafta ask!

***

AI neuroscience startup Vicarious announced that it has raised $50M in a round led by Khosla Ventures, according to VentureBeat.

The company is said to be using computational neuroscience to build better machine learning models that help robots address a wide variety of tasks. They focus on the neocortex, a part of the brain concerned with sight and hearing.

Does that mean Alexa will soon be able to fetch me a beer from the fridge??!

Written by turbotodd

July 26, 2017 at 8:36 am

IBM and University of Alberta Publish New Data on Machine Learning Algorithms to Help Predict Schizophrenia

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IBM scientists and the University of Alberta in Edmonton, Canada, have published new data in Nature’s partner journal, Schizophrenia1, demonstrating that AI and machine learning algorithms helped predict instances of schizophrenia with 74% accuracy.

This retrospective analysis also showed the technology predicted the severity of specific symptoms in schizophrenia patients with significant correlation, based on correlations between activity observed across different regions of the brain. This pioneering research could also help scientists identify more reliable objective neuroimaging biomarkers that could be used to predict schizophrenia and its severity.

Schizophrenia is a chronic and debilitating neurological disorder that affects 7 or 8 out of every 1,000 people. Those with schizophrenia can experience hallucinations, delusions or thought disorders, along with cognitive impairments, such as an inability to pay attention and physical impairments, such as movement disorders.

“This unique, innovative multidisciplinary approach opens new insights and advances our understanding of the neurobiology of schizophrenia, which may help to improve the treatment and management of the disease,” says Dr. Serdar Dursun, a Professor of Psychiatry & Neuroscience with the University of Alberta. “We’ve discovered a number of significant abnormal connections in the brain that can be explored in future studies, and AI-created models bring us one step closer to finding objective neuroimaging-based patterns that are diagnostic and prognostic markers of schizophrenia.”

In the paper, researchers analyzed de-identified brain functional Magnetic Resonance Imaging (fMRI) data from the open data set, Function Biomedical Informatics Research Network (fBIRN) for patients with schizophrenia and schizoaffective disorders, as well as a healthy control group. fMRI measures brain activity through blood flow changes in particular areas of the brain.

Specifically, the fBIRN data set reflects research done on brain networks at different levels of resolution, from data gathered while study participants conducted a common auditory test. Examining scans from 95 participants, researchers used machine learning techniques to develop a model of schizophrenia that identifies the connections in the brain most associated with the illness.

The results of the IBM and University of Alberta research demonstrated that, even on more challenging neuroimaging data collected from multiple sites (different machines, across different groups of subjects etc.) the machine learning algorithm was able to discriminate between patients with schizophrenia and the control group with 74% accuracy using the correlations in activity across different areas of the brain. 

Additionally, the research showed that functional network connectivity could also help determine the severity of several symptoms after they have manifested in the patient, including inattentiveness, bizarre behavior and formal thought disorder, as well as alogia, (poverty of speech) and lack of motivation.

The prediction of symptom severity could lead to a more quantitative, measurement-based characterization of schizophrenia; viewing the disease on a spectrum, as opposed to a binary label of diagnosis or non-diagnosis. This objective, data-driven approach to severity analysis could eventually help clinicians identify treatment plans that are customized to the individual. 

“The ultimate goal of this research effort is to identify and develop objective, data-driven measures for characterizing mental states, and apply them to psychiatric and neurological disorders” said Ajay Royyuru, Vice President of Healthcare & Life Sciences, IBM Research. “We also hope to offer new insights into how AI and machine learning can be used to analyze psychiatric and neurological disorders to aid psychiatrists in their assessment and treatment of patients.”

The Research Domain Criteria (RDoC) initiative of NIMH emphasizes the importance of objective measurements in psychiatry. This field, often referred to as “computational psychiatry”, aims to use modern technology and data driven approaches to improve evidence-based medical decision making in psychiatry, a field that often relies upon subjective evaluation approaches.

As part of the ongoing partnership, researchers will continue to investigate areas and connections in the brain that hold significant links to schizophrenia. Work will continue on improving the algorithms by conducting machine learning analysis on larger datasets, and by exploring ways to extend these techniques to other psychiatric disorders such as depression or post-traumatic stress disorder.

You can learn more about IBM Watson Health solutions here.

Written by turbotodd

July 21, 2017 at 9:21 am

Robots Moving East

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The robot wars are headed east.

TechCrunch is reporting that Japanese tech giant Softbank is buying robotics firms Boston Dynamics and Schaft from Alphabet.

Direct from the press release:

Masayoshi Son, Chairman & CEO of SoftBank Group Corp., said, “Today, there are many issues we still cannot solve by ourselves with human capabilities. Smart robotics are going to be a key driver of the next stage of the Information Revolution, and Marc and his team at Boston Dynamics are the clear technology leaders in advanced dynamic robots. I am thrilled to welcome them to the SoftBank family and look forward to supporting them as they continue to advance the field of robotics and explore applications that can help make life easier, safer and more fulfilling.”
– via SoftBank Group

The release also explains: “The transaction aligns with SoftBank’s investments in paradigm-shifting technology and its vision of catalyzing the next wave of smart robotics.”

But this likely isn’t just about robots for robotics’ sake. A recent CNBC story explained that Japan’s service sector accounts for 70 percent of its economic output, and yet its labor productivity is 40 percent less than in the U.S.

And Japan’s population is declining faster than any other country:

Economists argue that Japan either needs to accept more immigrants or put robots to work.
– via CNBC

Okay, robots, smoke break’s over, get back to work!

Written by turbotodd

June 9, 2017 at 9:49 am

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