An independent Windows Phone developer has created an app for Microsoft's mobile platform that will attempt to outmatch Apple's intelligent voice-controlled assistant Siri. Ask Ziggy for Windows Phone is a free ad-free mobile app that can perform similar tasks to the iOS 5 voice assistant. "Ask Ziggy uses Speech Recognition to translate human speech into transcribed text, which is displayed in a speech bubble. The transcribed text is analyzed for patterns to detect commands or general queries. Commands are interpreted and routed to routine phone tasks such as emailing, texting, calling, social network updates, and getting directions," said Shai Leib, the app's developer, told WPcentral.

Wouldn't it be great to be able to search videos for what people are actually saying instead of relying on tags or descriptions? Koemei (pronounced "co-may") aims to do just that through their cloud-based speech recognition software that rapidly transcribes video and audio, even if people have accents or more than one person is speaking. But the startup is also targeting the large quantities of media content from videoconferencing, webcasting, and classroom lectures being produced in business, government, and educational institutions, and by indexing the transcripts, video libraries will become easily searchable. According to the company, it currently takes about an hour for its system to automatically transcribe one hour of media at a cost of about $0.09 a minute, much cheaper than manual transcription, though user pricing for the service has not been announced. Building on 8 years of research, the startup comes out of the Idiap Research Institute in Switzerland, and is in the process of raising $1.5 million is a Series A round on top of its Angel funding since its 2010 launch.

Having recently turned a corner in profitability, Nuance (NASDAQ:NUAN) trades at a PEG ratio of 0.0762. For reference, Apple (NASDAQ:AAPL) has a PEG of 0.2012. Nuance is 1/60th the size of Apple. Nuance has an EV/EBITDA TTM of 25.07. Nuance has a Price/Sales ratio of 4.075.

Showcase, from Intelligent Financial Systems Ltd, includes examples of practical neural net use and some Java tutorials illustrating back-propagation networks.

Blog posts can be strange and unpredictable things. There are times when I pour a ton of energy and creativity into a post only to have it largely ignored. Other times I quickly and haphazardly put something together and it ends up attracting thousands of hits. Such was the case with my recent post, Must-know terms for today's intelligentsia. Owing to all the interest, feedback and requests, I've decided to revise the list and provide greater detail and links. I apologize for not providing this in the first place. Before I get into the list, however, I'd like to clarify the purpose of this exercise. First, I am trying to come up with a list of the most fundamental and crucial terms that are coming to define and will soon re-define the human condition, and that subsequently should be known by anyone who thinks of themselves as an intellectual. I admit that there's an elitist and even pompous aspect to this exercise, but the fact of the matter is that the zeitgeist is quickly changing. It's not enough anymore to be able to quote Dostoevsky, Freud and Darwin. This said, while my list of terms is'required' knowledge, I am not suggesting that it is sufficient. My definition of an'intellectual' also requires explanation. To me an intellectual in this context is an expert generalist -- a polymath or jack-of-all-trades who sees and understands the Big Picture both past, present and future.

Most people wouldn't want a message from work disrupting their day at the beach. But Eric Horvitz was so happy when it happened to him that he took out a camera and captured the moment in a photo. The e-mail message had been singled out and sent to the Microsoft senior researcher's mobile phone by a special program that he and others in his group developed. The program examined the message's contents, determined its importance and decided it warranted interrupting him during a family outing on Whidbey Island. The moment perfectly illustrated Horvitz's long-term vision for technology in the information age -- as something to augment and assist people, not overwhelm them.

And because AI students are trained in such a rich multidisciplinary environment, they have excellent career opportunities. To make a thinking machine is one of humanity's oldest dreams. And since Allan Turing?s 1947 lectures on AI, programmable computers seemed to be the best way to go. Expectations were extraordinarily high in the 1950s and '60s, but without major breakthroughs, the whole subject lapsed temporarily into obscurity. Now, advances in the cognitive sciences that are improving our understanding of the nature of intelligence, memory, and perception from the biological perspective, coupled with the ready availability of ever-faster computers, are creating a second spring for AI--and a mecca for multidisciplinary scientists.

Alan Turing, who probably got there first no matter how exotic your approach to artificial intelligence, once had the idea of "unorganized machines". He was thinking of possible ways that the initial neural networks might form a newborn baby's brain. One of his ideas was a collection of initially random logic gates that cold self-organize or be trained for particular tasks over time. He saw this as a possible approach to realize intelligent machines. We could implement such an idea today in hardware or software but what about using chemistry?

I am currently one of about 30 people working towards building an Internet for robots: a world-wide, open-source platform that allows any robot with a network connection to generate, share and reuse data. RoboEarth's goal is a proof of concept to show two things: That RoboEarth greatly speeds up robot learning and adaptation in complex tasks, and that robots using RoboEarth can execute tasks that were not explicitly planned for at design time. The vision behind the four year, Europe-funded project is much larger: Allow robots to encode, exchange, and reuse knowledge to help each other accomplish complex tasks. This goes well beyond merely allowing robots to communicate via the Internet, outsourcing computation to the cloud, or linked data: Unlike humans, robots excel at systematic data collection, so a system that allows robots to autonomously create meaningful knowledge and share it could provide a powerful feed forward to any robot's 3D sensing, acting and learning capabilities. For more information, have a look at the RoboEarth website.

A Cambridge University professor is developing a navigation system that does what most boyfriends can't: read your emotions, sense what's going on, and adapt to the situation. Charles is a robot that is more co-pilot than GPS device. Frustrated by unintuitive gadgets that aren't helpful--let alone interactive--Professor Peter Robinson, who leads the Rainbow Group working on computer graphics and interaction at Cambridge, developed an emotionally intelligent navigation system that can tell how you're feeling and respond accordingly. The system uses sensors and algorithms of predefined mental states to track facial cues, tone of voice, body language, and posture. Using this information, Charles can read human emotion with a 70 percent accuracy rate, which is on par with human ability, Robinson says in a YouTube video demonstrating his project.