Archive for July, 2011

Browser extension Hyperwords

Wednesday, July 27th, 2011

The browser plugin Hyperwords is based on the research of Doug Engelhbart and turns words and numbers into hyperlinks. Lets first take a look at how to use Hyperwords.

 

 

 

Hyperwords not only lets you jump to another page or another web site (like “normal” hyperlinks). Instead Hyperwords lets you interact with the word in several ways. After selecting text, a small blue ball and then a pop-up menu appear, offering reference, sharing and (currency) conversion, even translation options. These options can be customised and expanded to your taste.

Hyperwords allows us to set in context what we read, associate the words (and numbers) just like in an associative network (See Prof. Dr. Ulrich Reimer explanation of Lightweight Ontologies LWO).

You can download and install Hyperwords on Firefox, Chrome or Safari. Head over to hyperwords.net.

Computer reads manuals and learns how to take over the (virtual) world

Wednesday, July 20th, 2011

And not only that, it also learns language. Researchers have designed a computer system that can understand language, that is the instructions to play Civilisation II. The video games industry surely can’t wait to get their hands on this. Imagine this: Really smart game opponents.. (via MIT news).

Machine Learning Makes Twitter Smarter in Portuguese

Thursday, July 14th, 2011

Press Release

Brazilian Arquiware signs deal to use new machine learning SDK to enhance sentiment analysis of social media networks.

La Jolla CA | São Paulo – Marketing consumer products in Brazil is about to get a lot easier thanks to a small, innovative software company. Arquiware is combining artificial intelligence with natural language processing to enable companies to analyze feelings and opinions social media networks. They are among the first in the world to apply techniques to create tools that enable companies to understand the sentiments of customers.

“Many multi-nationals come to Brazil then realize that it takes more than understanding Portuguese to understand how a brand interacts with consumers.” said Luis Lima, President of Arquiware, “In fact, the diversity of Brazil makes it almost impossible to understand our market unless you use sophisticated tools to extract the true meaning of what people are saying about you.”

Arquiware will add ai-one’s Topic-Mapper SDK to build artificial intelligence into two existing products. SentimentWare and TopicExtractWare analyze text data from social media networks and news feeds. The new capability gives Arquiware clients the ability to understand how any given news event will impact the perception of a brand.

ai-one’s technology is used by telecom companies, security and law enforcement agencies to enable computers to read text in a similar manner to humans. “We are thrilled that Arquiware will apply our technology to social media sentiment analysis. They are ahead of the efforts I have seen in Silicon Valley,” commented Olin Hyde, VP of Business Development for ai-one.

About Arquiware DSC (Brazil), Arquiware is one of Brazil’s leading software companies specializing in application development using natural language processing (NLP) and text mining. Arquiware builds custom applications for numerous enterprise clients and sells commercial off-the-shelf products for sentiment analysis and text extraction. SentimentWare provides sentiment analysis of social networks using the Radian6 API. TopicExtractWare is a SaaS that summarizes the meaning of any corpus of text by distilling information into tag clouds. Visit Arquiware’s free sentiment analysis of Twitter feeds to determine the best samba school in Carnival.

Contact:  Luis Lima Phone +55-11-233-82742, email: lglima (at) arquiware.com.br web: http://www.arquiware.com.br

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Calling a support hotline?

Wednesday, July 13th, 2011

Then you might have IBM’s Watson helping you. So, maybe Star Trek’s talking computer is not so far off anymore, with Watson. IBM is looking to shop the technology around to industries like retail and customer service. Read more on Hemispheres Magazine.

Leader of Knowledge Management and Text Analytics Joins ai-one Partner Network

Tuesday, July 12th, 2011

Press Release

KAPS Group plans to use new machine learning SDK to build advanced knowledge management applications for enterprise clients.

La Jolla CA | Oakland CA – KAPS Group announced today they would start using ai-one’s machine learning technologies to build custom applications for large corporations and government agencies. KAPS specializes in designing and developing systems that add semantic intelligence to unstructured content. These systems range from enterprise search to sentiment analysis-based customer intelligence to knowledge management systems that enable organizations to capture and use the information that employees learn through years of on-the-job experience. These systems are becoming increasingly important as companies struggle to retain expertise as expert employees retire or leave the company.

Semantic Structure Key to Knowledge Management

Tom Reamy, Chief Knowledge Architect at KAPS, sees the market continuing to grow. “There is a growing realization that adding semantic structure is the only way to make sense of all the extremely valuable, unrealized content that resides in today’s organizations. This is true for the information and knowledge in documents and in the expertise of employees. And capturing, organizing, and structuring that information is what will drive companies to be more innovative, responsive, and profitable.”

The Value of Machine Learning

KAPS partnered with ai-one inc to gain access to software development kits (SDK) that enable programmers to build machine learning into other applications. These SDKs make it possible for computers to automatically read and learn the meaning of vast amounts of unstructured data by how words are associated with each other. For example, a system might read millions of emails on a drug discovery process to learn that two chemicals could achieve the same result – even though one of the chemicals was ignored by a research team.

“It is an honor to have KAPS as a partner,” said Olin Hyde, ai-one’s VP of Business Development, “they have a fantastic reputation for building state-of-the-art systems.” Previous KAPS clients include the FDA, GAO, Genentech, Visa and Amdocs.

About KAPS Group LLC

Led by Chief Knowledge Architect, Tom Reamy, KAPS is a group of knowledge architecture consultants with a wide range of skills and experience. The firm’s services include: text analytics categorization and entity extraction catalogs, taxonomy creation, design and implementation of metadata and controlled vocabularies, implementation of search, content management, and portals, and strategic consulting. Based in Oakland California, KAPS Group’s services are grounded in the creation and maintenance of the intellectual infrastructure of an organization. This intellectual infrastructure consists of a wide variety of content and knowledge structures from metadata and taxonomies to linked data and ontologies, information technologies, the information processes embedded within business procedures, and the information/knowledge needs and behaviors of individual people and social communities.

Contact: Tom Reamy Phone 1-510-530-8270, email: tomr (at) kapsgroup (dot) com web: www.kapsgroup.com

How to Use ai-one’s Machine Learning SDK: Insights from an expert programmer

Friday, July 8th, 2011

Ondrej Florian is one of ai-one’s leading experts in developing machine learning applications. Ondrej joined the ai-one Consulting Partner program in February 2011 and is currently building systems for financial services clients from his office in Basel, Switzerland. (Since this interview was posted, Ondrej has joined the ai-one team full-time).

Olin Hyde, ai-one’s VP of Business Development, recently interviewed Ondrej Florian who answered questions about his experience using ai-one’s Topic-Mapper SDK for machine learning.

Interview with Ondrej Florian GER Version- Für eine deutsche Version dieses Interviews finden Sie hier

What has been your experience using ai-one’s technology?

It has been a long journey. I was one of the first developers to use Topic-Mapper. At first I confused by what it actually does, more then anything. Now I love it. It is amazing because it opens so many possibilities to build really cool, smart applications.

What changed your mind about ai-one? Isn’t it hard to like a system after you have a rough start?

First I had to understand that artificial intelligence (AI) is not a magic bullet. Instead, it is a completely different way to look at programming.

They key is:  You need to find the core problem then see how to use AI to build a solution.

When I first started using it, I was frustrated with the results that Topic-Mapper gave me. It felt like the answers were wrong. The system seemed to have a life of its own. I fed it data and it gave me very perplexing answers. I thought, “That cannot be right.”

Then I realized that the system was only learning what it was exposed to.

If you feed it a little, then it only knows a little. The more you feed it, the more it knows.

I love it now. It makes me think in a different way. The possibilities for developing AI applications are only limited by my imagination.

What is so different about programming with ai-one technology?

It is more like a conversation than programming. You can think of AI as giving the computer an empty brain. With AI, it has the capacity to learn and act independently.

As a programmer, I am used to computers doing what I tell them to do. They only follow directions. With AI they start to find relationships independently.

With ai-one, I had to start thinking in a different way. You must think like teaching the computer – not programming it.

Inspiration is really important. The technology allows you to do so much more than what I understood at the beginning. It is not a problem with the technical documentation as such.  The API is very simple. Very straightforward.

The hardest part is to really understand two things:

  1. What are the core problems you want to solve with AI?
  2. What data is necessary for the system to solve the problem?

Forget your ‘assumptions’ you may have about how the system should work, don’t force it.

Once you have these two questions answered, then you can think about lower level questions, like: How can I make it easier for the system to read the data the same way I do?

The key to getting the most from the technology is to think about solving problems in a totally different way. I was told this at the start by Tomi Diggelmann (ai-one’s VP of Technology). He said: “It is important to get programmers to think differently or they will not understand what they can do with ai-one.”

How they should they think about problems? What is so different about it?

ai-one is very different than the traditional API – which is just a functional technology stack (e.g., LAMP). Traditional systems have a simple goal — to extract results. Programmers look for algorithms to solve a problem, using code to sort, match, extract data.  All you need to do is read the documentation, develop test cases, then build the application to meet the test cases. The hardest part is often making sure the data is in the right format, complies with your structure, and so on.

ai-one is different. It is very dynamic. First, you don’t have to worry about data formats. You just feed data into the holosemantic space. This is may be possibly the import command. It will accept any kind of data. It makes associations among all the elements as it ingests the data.

You curate the data by asking the system questions. It will reveal a lot of associations. You teach the system to know the data the way you know it by providing it with commands for context, associations and keywords.

Are there a lot of commands to know?

Really there are just four general functions you must understand: association, reverse_association, association_check and keyword. You use these commands to ask the system to tell you what it has learned from ingesting the data. It will give you results back. And they are sometimes confusing. At beginning you get nothing or things that are seemingly irrelevant. This is a sign that you have given the system too little information. If you give the system enough information it will give you easily over 80% correct answers the first time, without any teaching. The more data, the more accurate it becomes.

ai-one” listens” to the data then tells you what the data means. This eliminates the editorial bias of the programmer.

Yes, you can teach ai-one to give you the right answer – but this must be done carefully. Like an obedient child, the system will learn exactly what you tell it.

So you just feed the system information and it gives you meaning? That sounds too simple.

You must structure the data in the right way. Teaching is only to correct mistakes. Associations that should not be there.

I understand you were frustrated when you first used the SDK?

Yes. It was confusing to me because I had to teach rather than program. Under normal circumstances the machine will only do what it is programmed to do. In a way, ai-one’s SDK has a life of its own. It learns associations based only on the inherent semantic value of the data.

Programmers must learn why the data gives them the results. Programming with ai-one’s Topic-Mapper is almost like a conversation between the programmer and the system.

So how can programmers get up to speed quickly?

Working with ai-one is interactive. The machine will tell you what it sees – the programmer must be able to set aside assumptions and see how the machine is learning. The advantage of ai-one is that it will tell you how it is forming associations.

When you interact with the system – you must think past “bugs.” The results are not bugs – they are what the machine is seeing!  It sees the data from an inherent meaning – must be structured in way that the machine sees in the way you want it to see. Remember, the machine has no bias.

You must observe and learn from the results you are getting back.

People are still trying to determine how to use AI. It has been around for a long time. And it has failed many times. What makes this different?

From a programmer’s perspective, it comes down to inspiration. Rather than programming, you are influencing. Teaching the machine to augment human understanding.  ai-one’s SDK enables the programmer to find unknowns at the start – rather than when the program breaks from having an inadequate algorithm.

Do you have a case example where ai-one’s SDK has solved an unknown problem?

Many. For example, in risk management there are many ways for a person to cheat and steal from a financial institution. So how do you monitor and prevent it?

Traditionally, programmers would use SQL to run queries against a database and use rules to isolate variance then model the variance using algorithms. Risk evaluation is essentially static – you only program what you can know. This is doomed to fail. You can’t possibly know all the risk factors.

ai-one allows you to find the unknown – the unexpected relationships between data elements that are associated with risk. You let the system tell you what data elements are associated with risk then model those!

A lot of people don’t believe ai-one’s claims. They consider them too good to be true. How do you address this doubt and mistrust?

You can’t address it by arguments. Programmers like control. This is the problem. To control something, you must know a lot about it. When data gets really big and complex, it becomes impossible to know it enough to control it.

What changed my mind about ai-one is when I understood that the SDK enables me to understand big data so that I can use machine learning to augment systems to model data more accurately.

Statistical approaches are great at handling what is known.

ai-one’s technology is not a replacement for algorithms or programming – rather it is a way to enhance the value of all the great things programmers can do!

The way to address this skepticism is with demonstration, to take them through the same experience and let them discover it for themselves.  That’s why I signed up to help ai-one with the training for new programmers.

Crystal Reports Guru Embraces Machine Learning

Wednesday, July 6th, 2011

Press Release

DotNet Tech plans to use new machine learning SDK to bring advanced analysis of unstructured data into Crystal Reports services.

La JollaCA| Zurich| Berlin– Crystal Reports is about to get a lot smarter. Brian Bischof, widely regarded as the leading authority on Crystal Reports, just signed a deal to become an IT Services Consulting Partner with ai-one inc. The deal will give Bischof’s company, DotNet Tech, access to ai-one’s Topic-Mapper SDK to develop custom reporting tools that use artificial intelligence to report on unstructured data.

Crystal Reports, owned by SAP, is one of the most popular tools to create reports using information stored in databases. One of the biggest problems facing IT departments is reporting on data that is not easily categorized – such as feeds of text from the internet and social media.

ai-one’s Topic-Mapper enables Crystal Reports to read and ingest text in much the same was a human. This is the first deal that enables a consulting firm to build artificial intelligence into a common reporting tool.

“Gone are the days of trying to work around unstructured data,” said Bischof, “Now we can use ai-one’s Topic-Mapper to learn the inherent structure within any corpus.  Now we can process and include everything from Twitter feeds and Facebook postings into Crystal Reports using Microsoft’s Visual Studio.

Olin Hyde, VP of Business Development added “I’ve known Brian for a long time. He is a fantastic, visionary developer. I can’t wait to see what he does with Topic-Mapper combined with Crystal Reports and Visual Studio.”

About DotNet Tech, Inc., Led by founder, Brian Bischof, CPA is a systems consulting firm specializing in the development of advanced web-based applications using Microsoft’s .NET suite of development tools. Bischof is also the best-selling author of Crystal Reports books. Clients include University of California San Diego and more than 10,000 subscribers to www.CrystalReportsBook.com.

Contact:  Brian Bischof.  Phone 1-502-417-3681, email: public@bischofsystems.com web: www.dotnettech.com

About ai-one inc., ai-one provides technologies that enable programmers to build artificial intelligence into software programs. Based inSan Diego with offices inZurich andBerlin, ai-one’s “biologically inspired intelligence” is a virtual brain that learns without human intervention. Technically described as an adaptive holosemantic data space with semiotic capabilities, ai-one’s approach provides more accurate answers than competing technologies.  The Topic-Mapper™ SDK for text enables developers to create intelligent applications that deliver better sense-making capabilities for semantic discovery, lightweight ontologies, knowledge collaboration, sentiment analysis, artificial intelligence and data mining.

 

Contact: Olin Hyde, Phone: 1-858-381-5897, email: oh@ai-one.com, web: www.ai-one.com

 

Context aware computing could make gadgets smarter

Wednesday, July 6th, 2011

Are you in a meeting? Your phone will automatically switch to mute. This is Intel’s vision of coming devices. Small always-on gadgets enhanced with low power sensors could act more as your personal assistant, anticipating your needs and wishes. Context aware computing is to make computers (and gadgets) more in tune with us, the users – that they can sense the environment and react accordingly. How will your phone be your personal assistant? The magazine pcmag.com has an in-depth article about it or head over to gartner.com for the special report.