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It’s where forward-thinking managers should be focusing.
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Scoop.it!
Artificial intelligence has not only become an international arms race, competition has now heated up as companies look to adopt machine learning/deep learning at an unprecedented pace. But the conversation about AI has largely focused on pitting humanity against AI, instead of what happens when we bring together humans *with* AI. In this talk by a16z operating partner Frank Chen, given at the annual a16z Summit, Chen goes beyond the hype to look forward at how AI and automation will augment, enhance, create, and yes, replace humans…. but also highlighting what it is that makes us human to begin with.
Farid Mheirs insight:
WHY IT MATTERS: there are already a number of usable applications for AI in use today in organizations worldwide, large and small. This is one good list from a16z in an easy to listen video with great examples of innovative startups in the field.
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Every day there seems to be a new way that artificial intelligence (AI) and machine learning is used behind the scenes to enhance our daily lives and improve business for many of today’s leading companies. Here are 27 amazing, and practical examples of AI and machine learning.
Farid Mheirs insight:
WHY IT MATTERS: there are already a number of usable applications for AI in use today in organizations worldwide, large and small. This is one good list from Forbes.
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The child AI is really only capable of a specific task – image recognition. Using its AutoML AI, Google’s AI-building AI created its child AI using a technique called reinforcement learning. This works just like machine learning, except it’s entirely automated where AutoML acts as the neural network for its task-driven AI child.
Farid Mheirs insight:
WHY IT MATTERS: AI recent progress was made possible mostly by supervised learning: humans providing AI algorithms with the right kind of insight to understand the world. Reinforcement learning provides an enhanced level of improvement as it lets machine teach machine. This is one example. Expect more in the coming years and brace for exponential growth of this technology.
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In May, J.P. Morgan’s quantitative investing and derivatives strategy team, issued the most comprehensive report ever on big data and machine learning in financial services.
Farid Mheirs insight:
WHY IT MATTERS: AI will disrupt industries that had been left mostly alone by the digital Internet revolution: Finance, Accounting, Law, Medecine, etc. They are all industries that rely on visual or text analysis but require very simple processing to perform the most routine back office tasks. This report presents the impact in very detailed fashion and this summary is useful because it applies to many industries, if you adjust the terminology. It highlights one key element: learn to program and to analyze data because these are the jobs of the (near) future. For those crazy enough to read the 280 pages, here is the link: http://valuesimplex.com/articles/JPM.pdf
Graphics Design's curator insight,
January 30, 2018 7:51 AM
In the event that somebody says "please" and you hear "cheddar" recall that (record it). On the off chance that somebody says "entryway" and you hear "more" focus on that, don't disregard it or shut it out or accuse the speaker, simply perceive that it happened. Try not to contend with anyone or focus on their "you require a portable Hearing Aids". Watch your days concerning sound, what is the number on the TV volume control when you watch it without anyone else's input - what is the number when another person in the house is controlling
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Far from being incomprehensible, the principles behind neural networks are surprisingly simple. Here's a gentle walk through how to use deep learning to categorize images from a very simple camera.
Farid Mheirs insight:
WHY IT MATTERS: you don't need to be a mechanic to drive a car but it helps if you understand the principles of a car - engine, drive shaft, carburator, etc. - to help you when you buy or get serviced. Well I believe the same should hold true for technology in your computer or your cell phone. So no need to listen to these videos to use Apple Siri or Google assistant, but it will certainly make some of it feel less "magical".
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Andrew Ng, chief scientist at Baidu and professor at Stanford, said during his widely popular NIPS 2016 tutorial that transfer learning will be -- after supervised learning -- the next driver of ML commercial success.
Farid Mheirs insight:
WHY IT MATTERS: machine learning biggest advantage over human learning is that machines can share what they learn. For example, robots and self-driving cars can train using a simulator before they go in the real world. Moreover they can transfer what they learn in one field - say cat-dog image analysis - and apply it to another domain - say reading medical X-ray. This vastly improves the speed with which machines learn. This is a definitive advantage for machines that can ride digital technology's exponential growth. Ultimately, machines will become way more intelligent than humans because of their capacity to leverage the sum of all previous knowledge from birth, unlike us humans. We are doomed!
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The AI Index is an open, not-for-profit project to track activity and progress in AI. It aspires to be a comprehensive resource of data and analysis for policymakers, researchers, executives, journalists and others to rapidly develop intuitions about the complex field of AI.
Farid Mheirs insight:
WHY IT MATTERS: AI evolves rapidly and this report presents the state of the world (mostly the US at this time) as it relates to AI. Must read.
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This guide is for anyone who is curious about machine learning but has no idea where to start. I imagine there are a lot of people who tried reading the wikipedia article, got frustrated and gave up wishing someone would just give them a high-level explanation. That’s what this is. The goal is be accessible to anyone — which means that there’s a lot of generalizations. But who cares? If this gets anyone more interested in ML, then mission accomplished.
Farid Mheirs insight:
WHY IT MATTERS: this series of article present the fundamental technologies behind AI in a very simple and easy to understand way.
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This technology is called face recognition. Facebook’s algorithms are able to recognize your friends’ faces after they have been tagged only a few times. It’s pretty amazing technology — Facebook can recognize faces with 98% accuracy which is pretty much as good as humans can do!
Farid Mheirs insight:
WHY IT MATTERS: facial recognition libraries have made it very simple to include the feature in any system. Read the article to understand how facial recognition works then jump to this other post to try out the actual code to do it. https://blog.paperspace.com/facial-recognition-using-deep-learning/
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What AI can — and cannot — do for your organization.
Farid Mheirs insight:
WHY IT MATTERS: advances in computer vision due to deep learning algorithms has opened a world of possibilities for companies. Read this article and accompanying HBR posts. Great series.
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MouseLight is the most detailed map of the mouse brain yet. Scientists hope this brain map, and others like it, can help unravel the brain's mysteries.
Farid Mheirs insight:
WHY IT MATTERS: understanding of the human brain is essential to improve artificial intelligence. Advances in brain scanning technologies have allowed researchers to map 700 neurons in a ouse brain and the results are presented here. Look at the 2min video to understand what has been achieved.
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A new idea is helping to explain the puzzling success of today’s artificial-intelligence algorithms — and might also explain how human brains learn.
Farid Mheirs insight:
WHY IT MATTERS This article explains how deep learning neural networks learn to generalize and find patterns in their inputs by initially finding patterns then compressing to forget irrelevant elements and generalize what they've "learned". Well illustrated and relatively simple to understand.
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Teachable Machine, an experiment that makes it easier for anyone to explore machine learning. Teach a machine using your camera – live in the browser, no coding required.
Farid Mheirs insight:
WHY THIS MATTERS You have to try this to better understand how AI works. Moreover, the fact that the network runs on your browser is, by itself, quite the testament to the power of deep learning and machine learning to transform every application and device we own. Now go play!
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Tech giants including Baidu and Google spent between $20B to $30B on AI in 2016, with 90% of this spent on R&D and deployment, and 10% on AI acquisitions. AI investment has turned into a race for patents and intellectual property (IP) among the world’s leading tech companies.
Farid Mheirs insight:
WHY IT MATTERS This article from McKinsey provides an overview of the investments, improvements and priorities in AI and machine learning as of mid 2017.
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What is artificial intelligence? Why is it important? Why is everyone talking about it all of a sudden? If you skim online headlines, you’ll likely read about how AI is powering Amazon and Google’s virtual assistants, or how it’s taking all the jobs (debatable), but not a good explanation of what it is (or whether the robots are going to take over). We’re here to help with this living document, a plain-English guide to AI that will be updated and refined as the field evolves and important concepts emerge.
Farid Mheirs insight:
WHY THIS IS IMPORTANT Always very well written and informative articles, this one provides a good summary in simple terms.
Fouzia Raza's curator insight,
September 18, 2017 9:24 PM
R-The source of the article, The Quartz, is a fairly new business news resource with initial launchings occurring in 2012. The news startup longs to deviate from other media giants by focusing on “global business leaders -- digitally savvy, post-national executives who seek information that will help them better navigate the new global economy." Although in its infancy, The Quartz has a slight to moderate liberal bias, and hence might use emotive stylistic techniques that sway audiences to view issues through a certain perspective. A-In the article itself, the author fails to give an in-depth analysis of the drawbacks of AI and the looming fear of its potential to “circumvent any human attempts to shut them off.” The article thus fails to give a well-balanced account of the potential effects of increased use of AI. V- The article does succeed in providing reliable, factual information that is supported by research studies, experts such as Musk, and relevant historical events. The author also assesses the importance of AI by presenting its value to companies and hence the global economy. E- The author himself possesses a wealth of knowledge on the subject matter; this holds true when looking at the startup media as a whole. Its founding members include experts from The Wall Street Journal, Bloomberg, The Economist, and The New York Times. Given its deep focus on emerging technologies and the latest innovations, it is no doubt that The Quartz possesses a high level of expertise on the subject matter. N- It is evident that the author supports the growth of AI in the future by emphasizing the positives. The article does include several drawbacks, such as the possible biases that AI is often demonstrated to have. This is immediately followed up by possible solutions, which demonstrates the ability of improving the technology for further use.
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In October 2016, in a big milestone for artificial intelligence, Microsoft unveiled a system that can transcribe the contents of a phone call as well or better than human professionals. But while Microsoft's system had fewer transcription errors than the average human transcriptionist, it still couldn't best a team of trained humans. So, the world of academia fired back with a new challenge: Lower the error rate to below what human teams can do. Now Microsoft has done just that.
Farid Mheirs insight:
WHY THIS IS IMPORTANT Speech recognition is most important for business tasks and new computer interfaces that are small and pervasive (cannot fit a keyboard and mouse on a watch). This new research shows that it is possible to get 5.1% error rates on transcribing phone conversations. This is great but not yet error-free : expect more research to improve this extremely fast though.. This ushers in an era where your cell phone will record everything you say in a meeting - or elsewhere - and transcribe it for you to search the text for reference or recall the actual audio to show proof. Imagine how useful that can be when listening to a conference or class and take notes for you! Direct links to the Microsoft blog post and report are here: report: https://www.microsoft.com/en-us/research/wp-content/uploads/2017/08/ms_swbd17-2.pdf
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Intensive efforts to re-create human cognition will transform the way we work, learn, and play
Farid Mheirs insight:
WHY THIS IS IMPORTANT We often hear of AI and machine learning using neural networks and deep learning algorithms. In parallel, there are many other efforts being deployed to understand the brain to try and mimic it. This is a series of articles in IEEE Spectrum that provide just the right level of technical insights to help you understand where we stand on the matter. Many hours of interesting reading ahead!
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Researchers from the Facebook Artificial Intelligence Research lab (FAIR) recently made an unexpected discovery while trying to improve chatbots. The bots — known as “dialog agents” — were creating their own language — well, kinda. Using machine learning algorithms, dialog agents were left to converse freely in an attempt to strengthen their conversational skills.
Farid Mheirs insight:
WHY THIS IS IMPORTANT Humans may not be so smart after all if it takes a few simple neural nets to start to create new languages and communicate. The article is just a teaser, if you want to know more you have to go the the Facebook research group blog to read the full thing. https://research.fb.com/category/facebook-ai-research-fair/ https://code.facebook.com/posts/1686672014972296/deal-or-no-deal-training-ai-bots-to-negotiate/ https://code.facebook.com/posts/266433647155520/parlai-a-new-software-platform-for-dialog-research/
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Intelligence = Understanding + Reasoning
Farid Mheirs insight:
WHY THIS IS IMPORTANT This article explains key fundamental concepts about intelligence and provides real-world examples in the context of self-driving cars.
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Google quietly released an academic paper that could provide a blueprint for the future of machine learning. Called “One Model to Learn Them All,” it lays out a template for how to create a single machine learning model that can address multiple tasks well.
Farid Mheirs insight:
WHY THIS IS IMPORTANT The research paper last sentence may be the most important. IT states: "...our model shows transfer learning from Moreover the paper shows how complex neural networks have become and we can expect even more complexity in the future. Direct link to the research paper: https://arxiv.org/pdf/1706.05137.pdf
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80 private companies in cybersecurity that are using AI and categorized them into 9 areas of operation.
Farid Mheirs insight:
WHY THIS IS IMPORTANT AI is infiltrating all industries and domains. Security is one of the fields where AI may provide the most value because protection relies so much on flexible solutions that can adapt - which is where AI is most useful.
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What best distinguishes our species is an ability that scientists are just beginning to appreciate: We contemplate the future. Our singular foresight created civilization and sustains society. It usually lifts our spirits, but it’s also the source of most depression and anxiety, whether we’re evaluating our own lives or worrying about the nation. Other animals have springtime rituals for educating the young, but only we subject them to “commencement” speeches grandly informing them that today is the first day of the rest of their lives.
Farid Mheirs insight:
WHY THIS IS IMPORTANT This article provides a short summary of this new book, homo prospectus. It sheds light into how our brain works and why it is in fact prediction machine, always predicting the future.
I wrote about a similar book in the past, On Intelligence, which I also strongly recommend.
For more on intelligence posts I wrote, look here: http://fmcs.digital/blog/tag/intelligence/
Dave berkeley's curator insight,
June 8, 2017 8:49 AM
Always striving to live in the moment is sometimes difficult. I would add our brain also wants to dwell on the past as well.What say you?
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The most anticipated slide deck of the year is here. Key takeaways:
Farid Mheirs insight:
WHY THIS IS IMPORTANT This is an annual bag of goodies. Highlight #1: retail stores are closing at record pace while Amazon opens stores. This is such a huge trend because it transforms stores from a mini-warehouse into something else: a destination for experience, service, and training. Think Apple store with the highest sales per square foot, genius bar, classes and a showroom. Amazon has pushed its Amazon GO, no lines, no registers concept and it is rolling it out slowly. This is just the beginning...
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This report lays out the current state of AI for business, describes primary and emerging use cases, and states the risks, opportunities and organizational considerations that businesses are facing. It concludes with recommendations for companies thinking about applying AI to their own organizations, and a look at some of the business, legal and technical trends that are likely to shape the future. Key Findings
Farid Mheirs insight:
WHY THIS IS IMPORTANT The report provides one of the best diagram to explain where AI can be applied in businesses today.
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Curated by Farid Mheir
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WNHY IT MATTERS: everyone's wondering how to use AI within their organization. This paper suggests a 4-step approach to make this a reality, focussing on processes rather than technology.