Watson lämnar Jeopardy och förverkligar verklighetens möjligheter - Smarter Business 2013
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IBMs kognitiva system med artificiell intelligens öppnar upp för nya möjligheter. Watson är uppbyggt av system som lär sig, bygger kunskap på egna och andras fel och misstag och som programmerar om sig självt för att lyckas bättre nästa gång. En framtid som redan är här. Talare: Johan Ekesiöö, styrelseordförande, IBM Svenska AB Har du frågor eller vill du ha en kopia av presentationen? Kontakta Jesper Carlsten på bit.ly/SB13Jesper Mer från dagen på http://bit.ly/sb13se
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Watson lämnar Jeopardy och förverkligar verklighetens möjligheter - Smarter Business 2013
- 1. IBM Watson är konsten att förverkliga möjligheter Johan Ekesiöö, ordförande IBM Svenska AB Följ oss på @IBMWatson
- 2. Watson leder oss in i en ny era av system . . . Kognitiva system Programmerbara system Beräknande system
- 3. Watson leder oss in i en ny era av system . . . 1 Förstår naturligt språk och mänsklig kommunikation 3 Självlärande system från användarval och respons 2 Skapar och utvärderar bevisbaserade hypoteser
- 4. Kognitiva system i verkligheten Sjukvård Finans Detaljhandel Andra exempel
- 5. Tyck till om hur kognitiva system som Watson bäst kan användas! Eventforum: www.vivastream.com Twitter: #IBMSB13SE Email: johan.ekesioo@se.ibm.com
Editor's Notes
- Main Point: Watson represents a whole new class of industry specific solutions called cognitive systems. It builds on the current paradigm of Programmatic Systems and is not meant to be a replacement; programmatic systems will be with us for the foreseeable future. But in many cases, keeping pace with the demands of an increasingly complex business environment and challenges requires a paradigm shift in what we should expect from IT. We need an approach that recognizes today’s realities and treats them as opportunities rather than challenges. Further speaking points: For example, most digitized information of the past was structured. It was organized into tables, stored in easily identified cells in databases, and easily searched and accessed. Unstructured information was largely ignored as too difficult to utilize…and therefore it lay fallow. Similarly, traditional IT has largely limited itself to deterministic applications. 2+2=4. 100cm in a meter. Situations where there is only one answer to a question But this rules out a whole world of real world situations that have a more probabilistic outcome. It is very likely that the car will not start because of a dead battery but there is a chance there is a clog in the fuel line. It is very likely to be sunny tomorrow but it may rain. Traditional IT relies on search to find the location of a key phrase. Emerging IT gathers information and combines it for true discovery. Traditional IT can handle only small sets of focused data while IT today must live with big data. And traditional IT interacts with machine language while what we as users really need is interaction the way we ourselves communicate – in natural language.
- Main Point: At the core of what makes Watson different are three powerful technologies - natural language, hypothesis generation, and evidence based learning. But Watson is more than the sum of its individual parts. Watson is about bringing these capabilities together in a way that’s never been done before resulting in a fundamental change in the way businesses look at quickly solving problemsSolutions that learn with each iterationCapable of navigating human communicationDynamically evaluating hypothesis to questions askedResponses optimized based on relevant dataIngesting and analyzing Big DataDiscovering new patterns and insights in secondsFurther speaking points:. Looking at these one by one, understanding natural language and the way we speak breaks down the communication barrier that has stood in the way between people and their machines for so long. Hypothesis generation bypasses the historic deterministic way that computers function and recognizes that there are various probabilities of various outcomes rather than a single definitive ‘right’ response. And adaptation and learning helps Watson continuously improve in the same way that humans learn….it keeps track of which of its selections were selected by users and which responses got positive feedback thus improving future response generationAdditional information: The result is a machine that functions along side of us as an assistant rather than something we wrestle with to get an adequate outcome
- Main point: Watson use cases can be broadly broken into three classes: Ask, Discover, and Decide. Users can ASK Watson direct questions in natural language the same way they ask friends or colleagues questions. This is in contrast to reducing an inquiry to a set of keywords and receiving a set of links to sources where their answers may (or may not) lie. People who saw Watson’s victory on the quiz show Jeopardy! will be familiar with this simplest use case. Think of this as next generation chat. Second, users can DISCOVER new insights with Watson. Examples of this could be use of Watson as a research assistant such as a biotech investigator looking for the best way to treat a disease in a specific cohort of patients. Finally, users might use Watson to help them DECIDE on the best course of action. This would be for situations where users are looking for confidence-based recommendations for their next action when they have many options to chose from such as what course of treatment to prescribe to a patient or what investment choice to make.
- Main point: Join the conversation and take the next step. Further speaking points:. Get involved and learn more about ways that Watson can help your business today. Learn more on the web. Join the conversation on twitter and facebook. See how Watson was created and is having a real impact on youtube. And above all, contact your IBM representative to your priorities and goals and how Watson can help play a part in meeting them.