… when A.I.+ exceeds human intelligence
There are risk with super intelligent machines, but AI+ will also be able to solve many problems. Besides help at everyday tasks, it could possibly diminish diseases, accelerate our knowledge in science and compute solutions to world problems.
… when you can have a digital twin
By reading your mails, chats, social profiles and listening to your talks and speeches – your personal digital twin will know you so very well – she/he/it could handle many not so important decisions for you!
Claudio Weck & Co. is doing Research and Development in Artificial Intelligence and Machine Learning. We focus on Deep Learning with aspects from Neuroscience for analysing BigData towards AGI as well as Natural Language Processing for improved and very human-centric Human-Computer-Interaction. We like to solve the connection between World-knowledge databases (symbolic) and Deep Learning!
ai-claudio.com is quite new, but we already engage relentless in research, authoring articles, blogging, IT consulting and project management. Please feel free to browse through our posts and contact us in the form below.
from August 1st, 2015 please approach Claudio Weck’s new employer for any IT & strategy consulting requests. You will find the contact information to the employer either here, or in my professional network profiles, e.g. XING.
Big Data was a Buzzwords as well as a mostly undefined Fuzzword of the last years – now we have “Data Science”.
Whereas Big Data combines the 4 Vs (Volume, Variety, Velocity, Value = Analytics) Data Science is the science to work with big data, but here are some definitions:
Data Scientists are either statisticians with outstanding programming skills – or – software developer with outstanding knowledge of statistics.
while others say
Data Science is just a fancy word for the advanced linear regression
and a widly acknowledged definition is:
Data Scientists know the the Big Data tools, as well as the statistical Analytics combined with domain knowledge of the field of work they are in.
Talking about machine learning today doesn’t go without talking about distributed fault-tolerant data storage and query system.
Hadoop is an open-source Apache Project derived 2006 from Yahoo! and based on papers from Google in 2003, is such a widely used system. Even though it is basically ‘mostly just’ a filesystem it’s three biggest advantages are
At the core of Hadoop is the filesystem HDFS (Hadoop Distributed File System) which stores it’s data in blocks across all DataNode machines. The data is replicated usually on a (or more) machine in the same rack, as well as on an other rack. Clients connecting to Hadoop to read or write will first question the NameNode which will tell them at which DataNodes they can attempt to access.
The current Hadoop 2.x version rely on YARN (Yet another Resource Negotiater) for that and with data and server replication there is no single-point-of-failure anymore. On top of that Hadoop uses MapReduce as key/value database. Therefore Hadoop is great for lots of data retrievals and querying.
It’s drawbacks are: the data in HDFS is not editable, only append able, it takes a lot of configuration work and without any additions and it’s not for real-time queries.
Claudio’s Course Notes
Links from the lecture:
Artificial Intelligence is a huge topic at the ongoing Google I/O 2015.
Life from the keynote: most products discussed have new features heavily dependant on A.I.!
All-New Google Photos is using improved face and pattern recognition. Not only the face recognition was improved, which was already available in Google Picasa and other apps. But additionally and new to consumer photo album software – it also will use pattern recognition to add automatically searchable text tags.
Additional automatically cut and edited videos known as “auto awesome” will be improved as Google Photos “Assistant” – using A.I. internally to figure out which video sequences and photos to use.
Google Now has more then 1 billion information pieces able to show users to assist them at their current action. Simple via (A.I. powered) speech-recognition connected information are shown.
They have mentioned that since 2013, when speech recognition had a failure of about 23%, it’s down today to 8%. So we can expect this number to go down even further.
Len Epp is writing in A Vision Of A Driverless Future | TechCrunch about conclusions of the possibility of autonomous cars. Not only the drivers habits will change but the whole industry: shop on wheels, local services, no ownership of cars needed anymore, huge variation in sizes, …
So the AI powered self-driving cars will bring a huge change in our everyday life and for many businesses – great potential for many startups too.
Bill Gates agrees that we should be worried about artificial super intelligence!
Just a little after the ‘Future of Life Institute’ published an open letter on Research Priorities for Robust and Beneficial Artificial Intelligence, which states many risks and examples including many research ideas to avoid those risks. You can read our article Demonic A.I.! What are we afraid of? Solutions to the risks! about that.
Bill Gates: I am in the camp that is concerned about super intelligence. First the machines will do a lot of jobs for us and not be super intelligent. That should be positive if we manage it well. A few decades after that though the intelligence is strong enough to be a concern. I agree with Elon Musk and some others on this and don’t understand why some people are not concerned
Source: thisisbillgates @ Reddit
But he also is very exited and enthusiastic about A.I.:
Artificial intelligence is correctly perceived as a significant opportunity but also as an existential threat. A while ago Elon Musk urged us to be aware of A.I. , as it might be like calling for demons we might not be able to control. Also Cosmologist Stephen Hawking warned of the possible end of civilisation by AI. The dangers of which A.I. are very versatile.
About the dangers and far-reaching consequences was written very much in various media lately. As most readers have probably already read most of potential problems – here are solutions instead, from the brightest minds of A.I. and me.
(Starting soon) UC Berkeley’s introductory course of Artificial Intelligence (upper division course CS188) will begin and available to everyone online. You can join the classes for free or get certified for a minimum fee.
The lecturers will be Pieter Abbeel and Dan Klein, which both have masses of very positive student reviews and previous experience.
Stay also tuned for further information as well as lecture notes and possible discussions about this course on ai-claudio.com. If you can’t wait, have a look at UDACITY Machine Learning – 1 Supervised.
As young researcher we are extremely interested in the research and publication in Artificial Intelligence, especially Neuroscience for Machine Learning. Here are interesting Conferences and Events in 2015.
If you cannot attend, you still will be able get some of their papers and further resources on their linked event page.
Please feel free to send me further events or comments, they are as always appreciated!
02-05 January 2015, The Future of AI: Opportunities and Challenges in San Juan, Puerto Rico
21-23 January 2015, International Symposium on Artificial Life and Robotics (AROB 2015), in Beppu, Japan
25-30 January 2015, AAAI Conference on Artificial Intelligence (AAAI-15) in Austin, Texas, USA.
05-07 February 2015, Australasian Conference on Artificial Life and Computational Intelligence (ACALCI 2015), in Newcastle, Australia
25-28 March 2015, SMART Cognitive Science International Conference in Amsterdam, Netherlands
07-11 April 2015, International Neuroscience Winters Conference (17.) in Soelden, Österreich
08 – 10 April 2015, Evostar 2015 in Copenhagen, Denmark
19-22 April 2015, Spring Brain Conference, Bridging Neural Mechanisms and Cognition by FENS in Copenhagen, Denmark
22-24 April 2015, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2015) (23.) in Bruges, Belgium
19-20 May 2015 ICT Spring Europe 2015 with a AI&ROBOT AREA special in Luxembourg City, Luxembourg
26-30 May 2015, IEEE Robotics & Automation Societys Conference, (ICRA 2015) in Seattle, USA
25-28 May 2015, IEEE Congress on Evolutionary Computation (IEEE CEC 2015) in Sendai, Japan