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Mar 20 2018   1:44PM GMT

IBM Think 5 in 5: TED-style opener, five ‘paradigms to watch’

Adrian Bridgwater Adrian Bridgwater Profile: Adrian Bridgwater

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Director at IBM Research Arvind Krishna opened IBM’s Think 2018 conference in Las Vegas this week by introducing the firm’s ‘5 in 5’ presentation.

Delivered as an almost TED Talk style opener, this opening session was pleasing for three key reasons:

  • Female speaker/scientists outweighed the males.
  • No up-front IBM product pitches were delivered.
  • Absolutely nobody said ‘awesome’, or ‘super excited’ – not once.

Polymer chemist Jamie Garcia kicked off proceedings as master of ceremonies, a celebrated scientist in her own field, Garcia introduced the speakers one by one as they delivered their five-minute ‘pitch-explanations’.

The below notes are presented in paraphrased quote form in the speaker’s own voice – all the content represents quoted material, so quote marks have not been used.

#1 Blockchain crypto-anchors

Speaker: Andreas Kind, a specialist in crypto-anchors working at IBM Research.

From cinnamon to boiled eggs, we know that everything in this world has been copied these days. In some parts of the world, as many as 40% of parts in the car after market are fake. Drugs get recycled after bad storage procedures etc. The root of the problem is that global supply chains have become very complex because products are made in more than one country and assembled in others… and then sold in others still.

Blockchain can help us build a global provenance supply chain, but…

… anchors are needed to link cryptographic entries in blockchains to the physical objects [and services, presumably] in the real world.

We can use crypto anchors to validate everything from cars parts to medicine. Crucially, the DNA of every object [i.e. the physical shape and attributes] can be used to provide the information to track the provenance of everything tracked in blockchain.

#2 Quantum encryption techniques

Cecilia Boschini, lattice-based cryptography specialist

The appeal of mathematics is based upon the fact that once you learn the formula, you can work out any problem. Cryptography is the art of designing protocols to protect your data. When you have to send your credit card number to a store it is encrypted before it is sent. Today we use the most scientific approach to crypto systems based upon logic that makes breaking the system a very long and time consuming process that requires access to massive computing power.

So will quantum allow that power… so should we panic?

Well, we would need a quantum computer that has thousands of qubits… so we can now make problems that grow with us. To produce post-quantum theory we need to produce quantum resistant protocols.

This is what lattice is… a two dimensional lattice has a grid where the key is to find a specific point on a grid. In three dimensions with many layers, we start to get extremely complex.

#3 Robot powered AI microscopes

Tom Zimmerman, IBM research scientist – human/machine devices and paradigm scientist

By 2025 over half of the world’s population are going to be living in what we can call ‘water stressed’ areas. Plankton produce two thirds of the oxygen that we breathe, they are also the greatest sequester of carbon on the planet as they consume it for us when we produce it as a waste product.

Scientists has traditionally studied plankton by collecting them, treating them with chemicals and studying them while they live. We can combine remote sensing with AI to study plankton in their living environment.

#4 Bias in AI datasets

Francesca Rossi, IBM Researcher and university professor, global leader for AI ethics at IBM.

I think back to 30 years ago, when I went to first AI conference, we looked at making machines smarter with very little discussion related to the powers of those machines on our society.

Today I work with lawyers, economists, accountants and many other professionals to develop a multi-disciplinary view at what AI will do for us. Key concerns for AI are — bias, explain-ability and value alignment.

Once a system learns something out of a certain set of data, it will then try and generalize and apply that knowledge to many different areas. But if that set of data is not diverse enough, then the AI system will not have enough info.

But not all forms of bias are bad… some bias in domain specific skills (such as a doctor’s skills in medicine) is a type of bias that we do not want to eradicate. We predict that in the next five years we will eradicate bias and that only the systems that show a clean lack of bias will be the only ones that get used.

AI needs to be multi-disciplinary, multi-gender and multi-stakeholder.

#5 Quantum Computing

Dr Thalia Gershon, senior manager for AI challenges and quantum experiences at IBM.

Simulating the bonding of large molecules is tough because you have to simulate the relationship with every electron with every other electron. Quantum Computing gives us the power to do this kind of things as it encodes information into quantum states.

Many of our challenges today in computing are interdisciplinary problems – so we are now building systems with quantum properties to experiment with these issues.

Quantum Machines need to cooled down to -460 degree below Fahrenheit to keep them cool, so the task here is a big one.

Linear classical logical thinking does not help us in quantum exploration… we need to be able to think differently.

Computing classes will start to offer a quantum track within five years. Plus, we will also need to teach students in all disciplines what qubits are. Three different quantum computers are made available by IBM on the IBM Q Experience where there are three core programming options. AI and QC are not fully independent, we need to join these two worlds.

NOTE: We can (arguably) take these five areas (and others) as key pointers for software application development growth over the next five years.

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