WHY IT MATTERS: Digital Transformation
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WHY IT MATTERS: Digital Transformation
Going digital in your business? I select the best posts and highlight the reasons why it matters. Like it? Click "recommend" + register to get the digest in your inbox: http://fmcs.digital/newsletter-signup/
Curated by Farid Mheir
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Google’s #AI builds its own AI child and it’s better than anything humans have made - for recognizing images

Google’s #AI builds its own AI child and it’s better than anything humans have made - for recognizing images | WHY IT MATTERS: Digital Transformation | Scoop.it

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 Mheir's 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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JPMorgan's massive guide to machine learning jobs in finance: summary of a 280 page report.

JPMorgan's massive guide to machine learning jobs in finance: summary of a 280 page report. | WHY IT MATTERS: Digital Transformation | Scoop.it

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.
Titled, ‘Big Data and AI Strategies’ and subheaded, ‘Machine Learning and Alternative Data Approach to Investing’, the report says that machine learning will become crucial to the future functioning of markets. Analysts, portfolio managers, traders and chief investment officers all need to become familiar with machine learning techniques. If they don’t they’ll be left behind: traditional data sources like quarterly earnings and GDP figures will become increasingly irrelevant as managers using newer datasets and methods will be able to predict them in advance and to trade ahead of their release.

Farid Mheir's 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 

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Graphics Design's curator insight, January 30, 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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3 video #mustSee if you are into understanding #AI but not a scientist: How neural networks work, how convolutional networks work, Deep learning demystified

3 video #mustSee if you are into understanding #AI but not a scientist: How neural networks work, how convolutional networks work, Deep learning demystified | WHY IT MATTERS: Digital Transformation | Scoop.it

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 Mheir's 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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A great explanation of transfer learning and why it has become Machine Learning's Next Frontier #AI #MachineLearning

A great explanation of transfer learning and why it has become Machine Learning's Next Frontier #AI #MachineLearning | WHY IT MATTERS: Digital Transformation | Scoop.it

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 Mheir's 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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.@Stanford release the #AI index for 2017 full of data and analysis on the state of AI today #mustRead

.@Stanford release the #AI index for 2017 full of data and analysis on the state of AI today #mustRead | WHY IT MATTERS: Digital Transformation | Scoop.it

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.
AI is the new electricity, and is transforming multiple industries. The AI Index will help current generations track and navigate this societal transformations. It will also help future generations look back and understand the AI's rise.

Farid Mheir's 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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#weekendReading this 8-part blog post called "Machine Learning is Fun!" is a very good overview of what #AI technologies are all about

#weekendReading this 8-part blog post called "Machine Learning is Fun!" is a very good overview of what #AI technologies are all about | WHY IT MATTERS: Digital Transformation | Scoop.it

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 Mheir's 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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Modern Face Recognition with #DeepLearning and simple program anyone can try

Modern Face Recognition with #DeepLearning and simple program anyone can try | WHY IT MATTERS: Digital Transformation | Scoop.it

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 Mheir's 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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Puppy or Muffin? How #deepLearning enabled computer vision & made The Business of Artificial Intelligence possible via @hbr

Puppy or Muffin? How #deepLearning enabled computer vision & made The Business of Artificial Intelligence possible via @hbr | WHY IT MATTERS: Digital Transformation | Scoop.it

What AI can — and cannot — do for your organization.

Farid Mheir's 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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A 'Google Maps' for the Mouse Brain Details Neurons Like Never Before #video #singularity

A 'Google Maps' for the Mouse Brain Details Neurons Like Never Before #video #singularity | WHY IT MATTERS: Digital Transformation | Scoop.it

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 Mheir's 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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New Theory helps explain how Deep Learning works @QuantaMagazine @Wired

New Theory helps explain how Deep Learning works @QuantaMagazine @Wired | WHY IT MATTERS: Digital Transformation | Scoop.it

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 Mheir's 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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Now anyone can explore machine learning, no coding required

Now anyone can explore machine learning, no coding required | WHY IT MATTERS: Digital Transformation | Scoop.it
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 Mheir's 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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McKinsey's State Of Machine Learning And AI in 2017

McKinsey's State Of Machine Learning And AI in 2017 | WHY IT MATTERS: Digital Transformation | Scoop.it
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 Mheir's 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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hondaweary's comment, September 28, 2017 2:35 AM
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The Quartz guide to artificial intelligence: What is it, why is it important, and should we be afraid?

The Quartz guide to artificial intelligence: What is it, why is it important, and should we be afraid? | WHY IT MATTERS: Digital Transformation | Scoop.it

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 Mheir's insight:

WHY THIS IS IMPORTANT

Always very well written and informative articles, this one provides a good summary in simple terms.

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Fouzia Raza's curator insight, September 18, 2017 9:24 PM
From bioengineering to customer support, artificial Intelligence offers numerous advantages that tech empires such as Google, Microsoft, and Amazon have pounced upon as a window of opportunity. It is undoubtable that the field will experience tremendous growth in the coming decades, but not without some downfalls. This article gives a brief overview of artificial intelligence including its explosion, importance, and drawbacks. 

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.
Dave berkeley's curator insight, September 19, 2017 8:24 AM
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Microsoft's voice-recognition tech is now better than teams of humans at transcribing conversations

Microsoft's voice-recognition tech is now better than teams of humans at transcribing conversations | WHY IT MATTERS: Digital Transformation | Scoop.it

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 Mheir's 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:

blog: https://www.microsoft.com/en-us/research/blog/microsoft-researchers-achieve-new-conversational-speech-recognition-milestone/ 

report: https://www.microsoft.com/en-us/research/wp-content/uploads/2017/08/ms_swbd17-2.pdf 

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Can We Copy the Brain? a #series of technical papers on the subject via @ieeespectrum

Can We Copy the Brain? a #series of technical papers on the subject via @ieeespectrum | WHY IT MATTERS: Digital Transformation | Scoop.it

Intensive efforts to re-create human cognition will transform the way we work, learn, and play

Farid Mheir's 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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Facebook's AI accidentally created its own language & learned to negotiate in #chatbots

Facebook's AI accidentally created its own language & learned to negotiate in #chatbots | WHY IT MATTERS: Digital Transformation | Scoop.it

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 Mheir's 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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Why AI Works – Artificial Understanding

Why AI Works – Artificial Understanding | WHY IT MATTERS: Digital Transformation | Scoop.it
Intelligence = Understanding + Reasoning
In his book “Thinking Fast and Slow”, Daniel Kahneman discusses the idea that human minds use two different and complementary processes, two different modes of thinking, which we call Understanding and Reasoning. The idea has been discussed for decades and has been verified using psychological studies and by neuroscience.
Farid Mheir's 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 advances #AI with ‘one model to learn them all’

Google advances #AI with ‘one model to learn them all’ | WHY IT MATTERS: Digital Transformation | Scoop.it
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 Mheir's insight:

WHY THIS IS IMPORTANT

The research paper last sentence may be the most important. IT states: "...our model shows transfer learning from
tasks with a large amount of available data to ones where the data is limited". Much like with humans where people with more knowledge and general culture often are able to apply knowledge form one area to another. This appears fundamental in getting better AI solutions.

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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Cybersecurity’s Next Frontier: 80+ Companies Using Artificial Intelligence To Secure The Future In One Infographic

Cybersecurity’s Next Frontier: 80+ Companies Using Artificial Intelligence To Secure The Future In One Infographic | WHY IT MATTERS: Digital Transformation | Scoop.it

80 private companies in cybersecurity that are using AI and categorized them into 9 areas of operation.

Farid Mheir's 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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solidspug's comment, June 14, 2017 4:40 AM
nice
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Homo Prospectus: We Aren’t Built to Live in the Moment- our brain is always predicting the future #newBook

Homo Prospectus: We Aren’t Built to Live in the Moment- our brain is always predicting the future #newBook | WHY IT MATTERS: Digital Transformation | Scoop.it

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 Mheir's 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.

http://fmcs.digital/blog/on-intelligence-mustread-to-understand-frontal-cortex-architecture-what-makes-us-intelligent/ 

 

For more on intelligence posts I wrote, look here: http://fmcs.digital/blog/tag/intelligence/ 

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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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Weekend read: 350 slides Mary Meeker’s 2017 internet trends report - eCommerce is killing traditional retail #1

Weekend read: 350 slides Mary Meeker’s 2017 internet trends report - eCommerce is killing traditional retail #1 | WHY IT MATTERS: Digital Transformation | Scoop.it

The most anticipated slide deck of the year is here. Key takeaways:

  • Global smartphone growth is slowing: Smartphone shipments grew 3 percent year over year last year, versus 10 percent the year before. This is in addition to continued slowing internet growth, which Meeker discussed last year.
  • Voice is beginning to replace typing in online queries. Twenty percent of mobile queries were made via voice in 2016, while accuracy is now about 95 percent.
  • In 10 years, Netflix went from 0 to more than 30 percent of home entertainment revenue in the U.S. This is happening while TV viewership continues to decline.
  • Entrepreneurs are often fans of gaming, Meeker said, quoting Elon Musk, Reid Hoffman and Mark Zuckerberg. Global interactive gaming is becoming mainstream, with 2.6 billion gamers in 2017 versus 100 million in 1995. Global gaming revenue is estimated to be around $100 billion in 2016, and China is now the top market for interactive gaming.
  • China remains a fascinating market, with huge growth in mobile services and payments and services like on-demand bike sharing. (More here: The highlights of Meeker's China slides.)
  • While internet growth is slowing globally, that’s not the case in India, the fastest growing large economy. The number of internet users in India grew more than 28 percent in 2016. That’s only 27 percent online penetration, which means there’s lots of room for internet usership to grow. Mobile internet usage is growing as the cost of bandwidth declines. (More here: The highlights of Meeker's India slides.)
  • In the U.S. in 2016, 60 percent of the most highly valued tech companies were founded by first- or second-generation Americans and are responsible for 1.5 million employees. Those companies include tech titans Apple, Alphabet, Amazon and Facebook.
  • Healthcare: Wearables are gaining adoption with about 25 percent of Americans owning one, up 12 percent from 2016. Leading tech brands are well-positioned in the digital health market, with 60 percent of consumers willing to share their health data with the likes of Google in 2016.
Farid Mheir's 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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The Age of AI: How Artificial Intelligence is Transforming Organizations via @altimeter

The Age of AI: How Artificial Intelligence is Transforming Organizations via @altimeter | WHY IT MATTERS: Digital Transformation | Scoop.it

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

  1. When it comes to use cases, narrow and clear is better than new and shiny. Some of the most promising uses of AI today are highly specialized and highly vertical — from farming, to self-driving cars, to predictive analytics and precision medicine. In many cases, the most successful deployments will identify buying signals and churn signals and automate complex processes.
  2. AI will become a forcing function for an organizational data strategy. AI learns from vast amounts of data. Clean, accessible data is the foundation upon which successful AI is built. This means that data availability and accessibility should be early considerations when determining where to build, and where not to build, AI into systems.
  3. Ultimately, the opportunity (and risk) of systems based on machine learning is in their ability to sense, communicate, learn, act and adapt over time, and to connect with other systems.  It’s not just about devices that will play a song or order tickets to a concert.
  4. Governance, privacy, ethics, and trust are critical to the customer experience. Even with a relatively “narrow” AI, it’s important to understand that enabling machines to learn and act based on data and past experience has significant implications. It’s critical to scenario plan for AI deployments — not only for the legal and regulatory reasons, but to protect and enhance the customer experience.
Farid Mheir's 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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TensorFlow & Tensor Processing Units mean @Google will become the leader in #MachineLearning and #AI?

TensorFlow & Tensor Processing Units mean @Google will become the leader in #MachineLearning and #AI? | WHY IT MATTERS: Digital Transformation | Scoop.it

In just its first year, TensorFlow has helped researchers, engineers, artists, students, and many others make progress with everything from language translation to early detection of skin cancer and preventing blindness in diabetics. We're excited to see people using TensorFlow in over 6000 open-source repositories online.

Second-generation Tensor Processing Units (TPUs) are coming to Google Cloud to accelerate a wide range of machine learning workloads, including both training and inference. We call them Cloud TPUs, and they will initially be available via Google Compute Engine.

https://blog.google/topics/google-cloud/google-cloud-offer-tpus-machine-learning/ 

Farid Mheir's insight:

WHY THIS IS IMPORTANT

Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL) are impossible to neglect today and recent announcements from Google on TensorFlow and Tensor Processing Units mean that more companies and developers will be able to explore how AI and ML can be leveraged in their applications and industries. Expect acceleration in this field.

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A Peek at Trends in Machine Learning shows an explosion in papers recently

A Peek at Trends in Machine Learning shows an explosion in papers recently | WHY IT MATTERS: Digital Transformation | Scoop.it

Have you looked at Google Trends? It’s pretty cool — you enter some keywords and see how Google Searches of that term vary through time. I thought — hey, I happen to have this arxiv-sanity database of 28,303 (arxiv) Machine Learning papers over the last 5 years, so why not do something similar and take a look at how Machine Learning research has evolved over the last 5 years?

Farid Mheir's insight:

WHY THIS IS IMPORTANT

More research = more discoveries so we can expect even more practical uses of machine intelligence in the coming years...

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#fakeNews was nothing: AI algorithms are creating a frighteningly realistic fake future in #video

#fakeNews was nothing: AI algorithms are creating a frighteningly realistic fake future in #video | WHY IT MATTERS: Digital Transformation | Scoop.it
Thanks to machine learning, it’s becoming easy to generate realistic video, and to impersonate someone.
Farid Mheir's insight:

WHY THIS IS IMPORTANT

If you thought fake news was bad, well an era of fake audio and news clips is about to dawn on us. We need regulations to govern this otherwise there will be consequences in the political, business and personal fronts for sure...

 

Also see this other blog post on the subject, as it related to fake actors in movies, a much less troublesome use of the technology: http://sco.lt/8Eglqj

 

This field is moving fast if you compare this to a blog post of January 2016: http://sco.lt/85op5l 

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Curated by Farid Mheir
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