Our friends at Pokersites recently shared a blog & Infographic with us, titled:
Poker & AI: The Raise of Machines Against Humans. It details insights and research about the evolution of poker artificial intelligence, the history, as well as where it is now. They thought our community might be interested and asked us to share with you.
See the original post on their blog, here.
Enjoy!
Interview with David Brin by Shon Burton
SB) David, I’ve been a fan since I read “Earth” in my teen years. I’ve often reflected on how real some of the concepts in that book have become. For those who aren’t as familiar, could you give us a brief background on yourself and your work?
DB) Oh gosh. I’ve been rewarded for poking at concepts, so I guess you’d call me an intellectual rascal. I use my physicist chops for NASA, but that’s just part-time stuff. I’m best known for science fiction novels and stories – one of them filmed by Costner in ’97; (he cleverly brought it out the same weekend as Titanic!) But the most impudent thing I do – I’ve been killed for it, in the past — is meddling in fields where I’m un-credentialed… anthropology, addiction studies, national security, and lately perspectives on artificial intelligence.
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So, When Will AI Take Your Job? by Co-Founder, Shon Burton
AI going to replace 50% of human jobs according to a new CNBC article quoting Kai-Fu Lee, founder of venture capital firm Sinovation Ventures and former head of Google China. Peter Norvig, current Director of AI at Google has also commented on his concerns around AI decimating the job market recently. I think about these topics often as I am the founder of HiringSolved, an AI based software company which makes recruiting more efficient. So, when will AI come to take your job away and what can you do about it?
Don’t panic! This is our destiny. Building Artificial Intelligence to take away our jobs is a very natural part of the evolution of the human race. Humans are unique because we can create and use tools. The tools we create enable us to work more efficiently, which means that it requires less people to do the job with tools than it did without them. Therefore, the technology we create does some of the work for us, eventually replacing us and taking our jobs.
This isn’t a new thing. Consider the humble wheelbarrow, a 2000 year old technology which enables 1 person to carry the same amount of weight as 10 people. In making the task of carrying things easier and more efficient, the wheelbarrow is an example of technology taking away jobs. For a more recent example, take a look at the computer itself. Most people don’t know that the word “computer” was actually a job title before it was a type of machine. The word “computer” used to be the title of a human worker who made calculations manually. Machines took that job from us so quickly that most people don’t even realize that we used to be the computers. However, I would argue that nobody wants to give up their spam filter or start doing long division by hand and give up Excel.
OK, we have established that we as a species are special because we make technology, that it eventually takes our jobs and that this has been happening for a very long time. Even the AI programmers themselves are not safe. DARPA, the good people who brought us the Internet are working to automate some of what ML/AI engineers do. So, when will technology take your job? Let’s break this question down into a few hypothetical scenarios:
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About The Author
Shon Burton is the founder and CEO of HiringSolved, which builds AI based recruiting software like RAI. Mr. Burton is also the co-founder of MLconf, a leading independent conference on Machine Learning and The Artificial Intelligence Conference which is hosting an AI Startup Competition with Spark Capital for new companies applying AI in new products. If AI does take all of our jobs it will be partially his fault. As a concession, Shon would like to offer the reader a 20% discount code to The AI Conference in June in San Francisco.
Why is MLconf starting The AI Conference?
Why is MLconf starting the AI Conference?
MLconf started in 2012 as collaboration with Danny Bickson and Carlos Guestrin from the Machine Learning department at Carnegie Mellon University. Courtney asked Danny to speak at our geekSessions event on Big Data in 2011 along with Eric Bieschke the CTO of Pandora and a few other people tackling ML problems at scale. We went on to develop MLconf as an independent, vendor neutral event series, focusing on combining both practical and theoretical presentations on ML in real-world applications, while continuing to collaborate with Carlos and Danny on their Data Science Summit events which were acquired with Turi in 2016.
The market has changed dramatically in the last few years. In 2010, people were working in data science but it was being called everything from analytics to big data. When we started MLconf in 2012, the ML space was just starting to organize behind a few tool sets and open source frameworks. We wanted to create a community where everyone who was generally working in the space could meet and collaborate. Today, we host annual MLconf events in New York, San Francisco, Seattle and Atlanta and we see the MLconf events and the Machine Learning space growing dramatically each year with major support from top technology companies and a vibrant startup ecosystem.
When we look out a few more years, we see some form of ML based technology becoming a pervasive component of most applications in the same way that database technology is today. We’re thrilled to help create environments and communities where people connect, share and collaborate around this fast growing technology. At the same time we believe that AI deserves it’s own focus. Although there is invariably overlap between the two, we think that MLconf will continue to support the Machine Learning community as it explodes into every industry, improving existing applications and creating exciting new applications and software capabilities that have yet to be discovered and supporting the new industry that is being created around Machine Learning technology.
How will the AI Conference be different?
The AI conference will focus on emerging technology in Artificial Intelligence with a specific focus around projects, teams and people who are working on Artificial General Intelligence and related topics. In addition to deeply technical presentations on AI, we will also host presentations on topics in law, ethics, safety, and governance, as we believe those are interesting topics and important dimensions to address in this growing field. As we have always done with MLconf, we will engage the community to help us define what The AI Conference should be. Our first event will be in June of 2017. If you would like to participate, please contact us here. We’re looking forward to the conversation!
About the Blogger:
Shon Burton is the Co-Founder and Chairman of the Board of Directors at MLconf, and CEO at HiringSolved.
Books On Display At MLconf San Francisco
Morgan & Claypool:
- Active Learning
- Algorithms for Reinforcement Learning
- Analyzing Analytics
- Automatic Detection of Verbal Deception
- Bayesian Analysis in Natural Language Processing
- Essentials of Game Theory: A Concise Multidisciplinary Introduction
- General Game Playing
- Graph Mining: Laws, Tools, and Case Studies
- Graph-Based Semi-Supervised Learning
- Human Computation
- Introduction to Intelligent Systems in Traffic and Transportation
- Introduction to Semi-Supervised Learning
- Learning to Rank for Information Retrieval and Natural Language Processing, Second Edition
- Learning with Support Vector Machines
- Linguistic Structure Prediction
- Metric Learning
- Mining Latent Entity Structures
- Modeling and Data Mining in Blogosphere
- Natural Language Processing for Social Media
- Probabilistic Approaches to Recommendations
- Robot Learning from Human Teachers
- Semi-Supervised Learning and Domain Adaptation in Natural Language Processing
- Sentiment Analysis and Opinion Mining
- Statistical Language Models for Information Retrieval
- Statistical Relational Artificial Intelligence
- Syntax-based Statistical Machine Translation
- Trading Agents
Use “MLCON16” to save 20% off through December 31st, 2016: http://store.morganclaypool.
Cambridge University Press:
- Agarwal & Chen, Statistical Methods For Recommender Systems
- Bennett & Hugen, Financial Analytics with R
- Efron & Hastie, Computer Age Statistical Inference
- Flach, Machine Learning
- Fouss et al, Algorithms and Models for Network Data and Link Analysis
- Guenin e al, A Gentle Introduction to Optimization
- Leskovec et al, Mining of Massive Data Sets
- Warwick & Shah, Turing’s Imitation Game
Additional Machine Learning & Aritificial Intelligence Books on Display
- How to Create a Mind: The Secret of Human Thought Revealed, Kurzweil, Ray
- The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World, Domingos, Pedro
- Overcomplicated: Technology at the Limits of Comprehension, Arbesman, Samuel
- Artificial Intelligence Simplified: Understanding Basic Concepts, George, Dr Binto
- Rise of the Robots: Technology and the Threat of a Jobless Future, Ford, Martin
- Superintelligence: Paths, Dangers, Strategies, Bostrom, Nick
- Our Final Invention: Artificial Intelligence and the End of the Human Era, Barrat, James
- The Age of Spiritual Machines: When Computers Exceed Human Intelligence, Kurzweil, Ray
- Artificial Intelligence: The Basics, Warwick, Kevin
- The Singularity Is Near: When Humans Transcend Biology, Kurzweil, Ray
- The Inevitable: Understanding the 12 Technological Forces That Will Shape Our Future, Kelly, Kevin
- Our Robots, Ourselves: Robotics and the Myths of Autonomy, Mindell, David A.
Interview with Austin Marshall, Numenta
Our past Technical Chair, interviewed Numenta’s Austin Marshall about HTM’s Numenta’s view in Neural Networks/AI. [Read more…] about Interview with Austin Marshall, Numenta