IBM activities to push forward the Future of the IT Technology
I collected in a deck a number of thoughts about the Future of the IT Technology by observing and evaluating some of the breakthroughs that IBM Research generated mainly during last year or so.
The deck already on SlideShare and can be downloaded from here: https://www.slideshare.net/secret/CrZehA3UllNq3L
For what is concerned with the content. IBM Research, from my point of view, is a good observatory to do such a kind of projections and the method that I like to use to derive future visions is to start from a piece of work and try to project these results in the future assuming that they will grow and open the door to practical materializations in the standard business practice.
This exercise works well with IBM Research for a couple of reasons:
a) the wide range of activities that these teams perform that includes both basic research as well as practical works on hard business problems, and
b) the global and multi-cultural and cross-country perspective these labs have.
Of course, there is also another personal reason here: I played with insights coming from these labs and matching them with practical business problems for more than 20 years and this helped me to test and refine the observation methodology along the time 🙂
So which are projections coming out from this year results? Breakthroughs can be distributed into five main themes, such as:
Man & Machine Relation: Artificial Intelligence will integrate seamlessly into and enhance the workplace;
Machine Intelligence : AI will have enhanced reasoning abilities and will be widely distributed – helping us make decisions instantly;
Transactions : Blockchains will do for trusted transactions what the Internet did for Information
Problem Solving: New methods of computing are emerging to solve problems that classic machines cannot even attempt or consider more effective ways to solve a problem;
Cyber Security: Within next few years most of the today’s cybersecurity methods and protocols will be breached, so we need to act now.
Here under is a short introduction to each theme highlighting also relevant research activities and projects in each area form which we speculate about future IT evolution.
The Future of Man & Machine relation
Artificial Intelligence (AI), more than other things, is entering and deeply and influencing the relation between humans and machines. AI can be considered a general purpose product that could help to transform other products and services. The future trend here is that it will be seamlessly integrated and enhance the workplace as well as technologies with which we interact with in our homes.
It is no more a matter of how much smart are becoming machines to take or do a human job, rather, it is more a time in which humans are recognizing human limits (ops!, once again) and look for an help. Machines, as in the past, are not replacers of our duties, rather they are complementing and improving our expertise to cope with the increasing complexity of our society challenges. With AI we can do “more with less”, and in a society that is carefully look at sustainable principle and recognize the intrinsic limits of natural resources this is quite relevant topic.
Which is the trajectory? To have a seamlessly integration a large part of the relation between machine and humans will be digitalized. It will involve not only physical aspects, rather, also soft parts of the interaction. In one word the traditional human-computer interface is going to be transformed.
For example, “Digital humans”, as Soul Machine is demonstrating will come out from Hollywood movies and appear in other contexts. Digital humans could represent a new extreme of this relation. Digital humans could be our new kind of computer interface to interact with in next future in our personal homes as well as workplaces. Behind a Digital Human will operate advanced Machine Intelligence skills starting from specialized abilities such as sighting, high accurate speech ability as well as apply complex forms of reasoning to the textual language like unraveling Language Patterns.
Relevant works and systems in this area area:
- Soul Machine Digital Humans: https://www.youtube.com/watch?time_continue=2&v=AzPs7GfOkew
- Soul Machine Baby 5.0 – https://www.youtube.com/watch?v=yzFW4-dvFDA
- Soul Machine’s Greg Cross Presentation https://www.facebook.com/bwnet.fans/videos/10154882117121837/
- Air New Zeland Digital Human Call Center Agent Project https://www.ibm.com/blogs/ibm-anz/digital-humans
- IBM Research Debating Technologies http://www.research.ibm.com/haifa/dept/vst/debating.shtml
- IBM Research Unraveling Language Patterns http://www.research.ibm.com/haifa/dept/vst/grasp.shtml
- IBM GRASP: Rich Patterns for Argumentation Mining, Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing Copenhagen, Denmark, September 7–11, 2017. http://aclweb.org/anthology/D17-1141
- IBM Research Computer Vision activities: http://www.research.ibm.com/cognitive-computing/computer-vision/
- IBM Research Cognitive Movie Trailer https://www.ibm.com/blogs/think/2016/08/cognitive-movie-trailer/
- IBM Research AI technology auto-curates golf highlights at the 2017 Masters Tournament https://www.ibm.com/blogs/research/2017/04/ai-technology-auto-curates-2017-masters/
- IBM Medical Imaging Analytics and Solutions http://www.research.ibm.com/haifa/dept/imt/mia.shtml
- Learning to Make Better Mistakes: Semantics-aware Visual Food Recognition https://dl.acm.org/citation.cfm?id=2967205
- IBM Research Distributed deep Learning https://www.ibm.com/blogs/research/2017/08/distributed-deep-learning
- PowerAI DDL – https://arxiv.org/pdf/1708.02188.pdf
- IBM Research – https://www.ibm.com/blogs/research/2017/03/speech-recognition/
- IBM Research Voice Creator: http://www.research.ibm.com/haifa/dept/imt/ivvc.shtml
The Future of Machine Intelligence
On the other side Machine Intelligence has been evolved rapidly during last years. It already works in several practical areas. Major advancements in this area are connected with mutual and positive combination of three factors that have been developed during last 60 years: better algorithms, huge quantity of (digital) data and improved computing power.
It is interesting, once again, to observe that major improvements came out when we observed mother Nature and take inspiration from her. Deep neural network models, for example, are inspired by our brain organization and are the ones that from the algorithmic point of view are pushing the machine intelligence at high quality results in some practical areas, in recent years.
Deep neural networks are fascinating also for another reason: they are an example of “less is more” technology: a simple model could obtain great results when it is supported in the right way. In the case of Deep neural networks, the supporting context is provided by the abundance of digital data and by the abundance of the computational power. They are interesting also for the opposite reason: we experience their limit too as we experience our (human) limits everyday.
Deep neural networks are limited toys, at the end of the day, they are a mechanistic way to mimic just the surface of how we perceive things.
Behind the curtain there is much more to mimic and investigate: our symbolic thinking, our ability to learn cross-domain, or our way to learn from just ONE example thanks to our common sense reservoir. The future of the other two elements of the equation, such as Data and Computing, are not at the final stage to support the future of Machine Intelligence. They are evolving and adapting too. How? Soon we are going to utilize one of the basic building block selected of the Nature to represent information with 1 atom to represent 1 bit of information. Current systems represent 1 bit using 100.000 atoms, researchers foresee that this new representation will improve 40% or storage systems. In addition, we are new ways to make a computation that could imitate our analog (and not digital) ability to manage things. The trajectory here is that we are going to continue to improve computation and storage efficiency of our IT systems to support Machine Intelligence tasks order of magnitude during next years.
Relevant works and systems in this area are:
- IBM Researchers Store Data on World’s Smallest Magnet — a Single Atom https://www-03.ibm.com/press/us/en/pressrelease/51787.wss
- The future of AI debate Technology – https://www.ibm.com/watson/advantage-reports/future-of-artificial-intelligence/ai-innovation-equation.html
- Learn to trust artificial intelligence systems: https://www.ibm.com/blogs/think/2017/01/ibm-cognitive-principles/
- The world’s first five-nanometre silicon chip. A finger-nail sized chips with 30 billion transistors. https://www.ibm.com/blogs/think/2017/06/5-nanometer-transistors/
- IBM Research Brain Chip Neuromorphic Computing – http://www.research.ibm.com/articles/brain-chip.shtml
- IBM Research Gesture recognition at Low power devices – https://www.ibm.com/blogs/research/2017/07/brain-inspired-cvpr-2017/
- IBM Research new TrueNorth project update: U.S. Air Force Research Lab Taps IBM to Build Brain-Inspired AI Supercomputing System https://www-03.ibm.com/press/us/en/pressrelease/52657.wss
- IBM Research Phase Change Memory: In-memory Computing with 1 Million Devices for Applications in AI – https://www.ibm.com/blogs/research/2017/10/ibm-scientists-demonstrate-memory-computing-1-million-devices-applications-ai/
- IBM and MIT to Pursue Joint Research in Artificial Intelligence, Establish New MIT–IBM Watson AI Lab – http://mitibmwatsonailab.mit.edu/
The Future of Transactions
Nowadays, we are greatly utilizing machines that are able to compute and collecting their benefits mainly asking them to support us in doing a simple job: helping us to do transactions. Helping us selling and buying goods, or things, or services or even exchanging a piece of knowledge are good examples of transactions. We learned from our primitive age that encouraging individuals and communities to exchange things was an effective way to improve our societies and let them survive and flourish.
Supporting us in exchanging things at local or at global level and managing such a complexity is one of the main jobs of our computers that contributed to grow our economies during last 50 years or so.
We created an outrageous huge network of interconnected entities in which each of us, at individual and group level, such as companies and organizations, is part of. We are the nodes of an enormous network. Some nodes act as content providers or sellers and others as content receiver or buyers, but a huge number of nodes act as simple pass through or intermediators adding a modest value in the transaction itself.
The key question for the future of the transaction world is: could we simplify this model? Could we simplify the network complexity and reduce the number of nodes building intelligent bypasses? This technology answer to this for a growing number of researchers has already a name: Blockchain.
Blockchains are quickly reaching the “Chasm” point that in terms of Geoffery Moore means move this technology from visionaries to pragmatists. What is next in this area? The trajectory here is not simply replacing a way to implement a transaction system more efficiently to let, for instance, move a thing from point A to point B more quickly. To convince pragmatists you need to generate value or reduce costs along the transaction, significantly. Again the combination of the Machine Intelligence with Blockchains is the ideal candidate to do that. So the trajectory in this case will be the creation of a new transaction system that will autoregulate itself leveraging AI. A small but important part of this will be played by efficient modalities to connect physical entities and virtual blocks into a chains that represent uniquely that entities. Crypto anchors are the answer to this last problem. They extend blockchain’s Value Into the physical realm. For example, tamper-proof signatures will authenticate products, from medicine to diamonds and make counterfeit nearly impossible.
Research works and systems in this area are:
- Welcome to the Blockchain economy! Source IBM IBV Studies https://www-935.ibm.com/services/us/gbs/thoughtleadership/blockchainlibrary.html
- How IBM Research combines AI and Blockchain: https://www.ibm.com/blogs/research/2017/05/power-blockchain-watson/
- Resilient Consensus Protocols for Blockchains https://www.ibm.com/blogs/research/2017/10/resilient-consensus-protocols-blockchains/
- IBM Research crypto Anchors for Diagnostic devices: https://www.zurich.ibm.com/st/precision_diagnostics/cryptoanchors.html
The Future of Problem Solving
The way we make computing is evolving not only in terms of improved capabilities but the Nature inspiration job is working hard here trying to create new efficient ways to evolve current system rather it is helping is to create a new kind of problem solvers or computing systems.
We learned during last century that exist Physical laws that we cannot directly experience with our senses but exist and work for or with us, as quantum mechanics.
At the nano scale strange things happen that we cannot interpret with our classic eyes. Do you remember Flatland the romance of Edwin Abbott Abbott? (https://en.wikipedia.org/wiki/Flatland). The the new Nature imitation horizon here is how we can renew our computing problem solving ability leveraging quantum physics laws and proprieties?
This is a not easy job as decades of studies demonstrate but something here is happening. The trajectory here is that new practical quantum computers, that are inspired from quantum mechanic laws, could accelerate our classic computing systems and solve problems that with our classic systems we can not think to considered.
New styles to solve a problem are also emerging in other areas as the ability to perform computing platforms by assembling and mashing capabilities of small devices such as the smartphones we have in our pockets, an area that is known ad edge computing. The idea behind edge computing is to process the data right where it is generated. A stadium has potentially more raw capacity than some of the most powerful supercomputers in the world when it’s full of twenty thousand people carrying smartphones that sport a powerful CPU, array of sensors, storage and multiple radios for communications – and can be connected to one another.
Add tablets, drones, connected vehicles, and other smart devices into the mix, and you have beginnings of the next paradigm of computing.
Research works and systems in this area are:
- IBM Quantum Computing – https://www.ibm.com/blogs/research/2017/11/the-future-is-quantum
- Quantum Computing Barrier https://www.ibm.com/blogs/research/2017/10/quantum-computing-barrier/
- IBM Research Edge Computing – https://www.ibm.com/blogs/research/2017/02/bringing-edge-computing-to-life/
- Mesh Network Alerts from IBM and The Weather Company – https://www.youtube.com/watch?time_continue=5&v=IITqVRWvDAw
- IBM Research NanoDLD device – https://www-03.ibm.com/press/us/en/pressrelease/50275.wss
The Future of Cyber Security
Finally, a small but a big point to consider at the same time: how to protect us and our digital twins in this new digital horizon?
Security is not only a technology but the key element to protect our changing life like an additional immune system for the digital world. The trajectory here includes new ways to see security not only as an isolated defensive act we can activate like activating a firewall. Rather protect our digital security is a much more a global and systemic phenomena and once again, Machine Intelligence, is the key ingredient to build such immune system. Interesting works to highlights in this are how Artificial Intelligence is combined with Security to generate new and advanced contrasting tools as in the case of Cognitive Cyber Security systems that provides 50% faster analysis time of threats. Finally, two interesting angles also to consider are works in data cryptography area, the main tool that is our main barrier to contrast the inappropriate or fraudulent access to individuals and organizations data.
Here are emerging the advancement of a real-world usability of the Full Homomorphic Encryption, invented by an IBM Researchers last decade, that is the natural candidate to big challenges such as how to share your sensitive data in a way that preserve the privacy of the data donors, without undermining the utility of the data or impeding its convenient dissemination? Or how to perform a large scale privacy preserving analysis of data in an untrusted cloud environment or across multiple users?
Research works and systems in this area are:
- Identify and Understand threats with Watson for Cyber Security – https://www.youtube.com/watch?v=O4qftNyqiQA
- IBM QRadar Advisor with Watson – https://www.ibm.com/us-en/marketplace/cognitive-security-analytics#product-header-top
- AI is the future of cybersecurity – How Watson helps detect threats faster and better protect your organization – https://www.ibm.com/blogs/watson/2017/08/ai-is-the-future-of-cybersecurity-how-watson-helps-detect-threats-faster-and-better-protect-your-organization/
- Cognitive and Autonomic Cyber Defense https://www.sto.nato.int/publications/STO%20Meeting%20Proceedings/STO-MP-MSG-143/MP-MSG-143-24.pdf
- Sogeti Luxembourg – Reducing threat investigation and root cause determination from three hours to three minutes (Sogeti SOC analysts were 50 percent faster in analyzing information) http://ecc.ibm.com/case-study/us-en/ECCF-WGC12505USEN
- Efficient implementation of fully homomorphic encryption http://patft.uspto.gov/netacgi/nph-Parser?Sect1=PTO1&Sect2=HITOFF&d=PALL&p=1&u=%2Fnetahtml%2FPTO%2Fsrchnum.htm&r=1&f=G&l=50&s1=8,565,435.PN.&OS=PN/8,565,435&RS=PN/8,565,435
- Source: The 2nd Comparison on Critical Assessment of Data Privacy and Protect Secure Genome Analysis http://www.humangenomeprivacy.org/2015/slides/003_iDASH%20workshop%202015_setStage.pdf
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