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Artificial intelligence is very interesting sector at the moment and it is developing at sky rocket speed.
Behind artificial intelligence, besides “an ancient wish to forge the gods” as Pamela McCorduck, who wrote Machines Who Think (1979) said. There is the assumption that the process of human thought can be mechanized. This belief emerged with the rationalists as Gottfried Leibniz who assumed that human reason could be reduced to mechanical calculations. This is the sense of the famous quotation of Thomas Hobbes in Leviathan: "reason is nothing but reckoning". Basically, we can talk about artificial intelligence about any device that perceives its environment and takes actions that mime “cognitive” functions that humans associate with other human minds, such as “learning” and “problem solving”.
The genesis of artificial intelligence and its historic actor: IBM
Artificial intelligence is born during the Dartmouth Conference of 1956 organized by the scientists Marvin Minsky, John McCarthy, Claude Shannon and Nathan Rochester from IBM. The proposal for the conference included this assertion: "every aspect of learning or any other feature of intelligence can be so precisely described that a machine can be made to simulate it". This conference is the syncretisation of previous discoveries made earlier in the century. The first one is the one of Kurt Friedrich Gödel helped by two mathematical tools, the Turing machine and Lambda calculus. While he was proving that there is limits to what mathematical logic can accomplish, he proved that within these limits, any form of mathematical reasoning could be mechanized and so described digitally (i.e., all-or-nothing signals). The second one is the information theory of Claude Shannon which described digital signals (i.e., all-or-nothing signals). Then Norbert Wiener’s cybernetics described control and stability in electrical networks. Finally, neurology had shown that the brain was an electrical network of neurons that fired in all-or-nothing signals. This is the relation between all this discoveries that has suggested the possible creation of an electronic brain.
We were far from a real intelligent machine. However, only one year after, in 1957, the American psychologist Frank Rosenblatt set on a computer the abilities of learning of a machine, the Perceptron. While things were getting increasingly serious, it is only in 1968 that the computer HAL, in “2001: a space odyssey”, introduced to the public the artificial intelligence. Public finally became totally aware of this breakthrough and its possible consequences during one of the milestones of the artificial intelligence’s history. The day when Deep Blue, a computer conceived by IBM, defeated in 19 moves the six-fold world champion Kasparov the May 11, 1997.
It leads us to consider a major actor in the development of AI, the American company IBM. Whose development is intrinsically linked to the improvements and the enhancements of the sector. While the first generation of AI researchers already used computer as the IBM 702 in their researches on AI. The whole world realised that the firm was no longer a PC constructor but a major actor in AI when in 2011, Watson, its question answering system, defeated the two greatest Jeopardy! Champions, Brad Rutter and Ken Jennings, by a significant margin. But the software Watson is a part of a larger development programme, the DeepQA research project. Its objective is to grasp real language and its underlying significations. The philosophy of this research project is that real intelligence will emerge from the development and integration of many different algorithms each looking at the data from different perspectives. The functioning of the DeepQA software is as below:
The development of the Deep QA software (on which Watson will rely on) started in 2007. It is the result of decades of work towards this direction, the one of AI, and it is until that day one of the most succeeded one. It has lead IBM to unveil in 2009 the project Watson. This project is so important for IBM that in 2014, IBM has launched its subsidiary IBM Watson Group in which it has invested 15 billion of dollars between 2010 and 2015. For IBM, it is a gamble on the future because all the other sectors in which IBM is involved shows a negative growth. To win this gamble, Watson didn’t remain a simple cheeky, it has been improved to satisfy much bigger stakes. It is now able to diagnose a disease in a patient or to make financial analysis. It embodies by itself the huge amount of opportunities that AI is carrying into our lives.
An unexpected set of improvements always closer to our daily lives
Indeed, if a lot of people are still or became afraid with respect to the ability to control AI. AI represents in first instance the biggest technological revolution to be made in our century. As the invention of the steam engine leads to the first industrial revolution in the middle of the eighteenth century in England. As the discovery of oil and the production of electricity had been the fertile ground on which throve the second industrial revolution in the middle of the nineteenth century. The development of AI is paving the way for a major upheaval in almost every fields of the economy. It carries with it a cluster of innovations as would say Joseph Schumpeter, a major economist of the 20th century which considered that innovation rhythms economic cycles.
Let’s begin becoming more precise. AI allows to gain productivity, to enhance customer’s satisfaction, it can advise teams in the bank sector, in the marketing sector with some algorithms of recommendation based on customers’ data (which are every day more numerous, so it still allows a vast ground of improvement) and it can also drive autonomous cars. AI can now predict studying our credit card behaviour if we will divorce next year said Matthieu Courtecuisse CEA of Sia Partners. It can also help call centres to know its customers’ emotions on line to assist the operator. According to him, human and IA shouldn’t be opposed, we must work on paradigm of the increased intelligence, it is positive.
To handle more concretely the new possibilities that unleashes AI, let’s focus on the new capabilities of Watson. For example, Woodside Energy, the Australia’s largest independent oil and gas company, has decided to upload into Watson ion IBM Cloud 38,000 documents, the equivalent of 30 years of practical engineering experience. Employees simply must ask Watson a question in natural language such as: “What is the maximum weight of a helicopter landing on the platform?”, and Watson find results from previous experience uploaded and employees can take informed decisions. The applications of IBM’s question answering system Watson are even still unsuspected. Take the example of E.&J. Gallo Winery. It farmed in California for more than 80 years, a region in which water is as important as scarce. Thanks to a satellite looking down on the vineyard, each block of vines gest its own personal irrigation plan based on weather data and soil moisture levels. This is also powered by IBM Cloud computing, a set of cloud computing services for business offered by IBM, in which Watson gathers data from weather satellite and historic information about the company. Thanks to this system, the products are superior, and watering is tailored for precise areas. It has improved water efficiency of the largest family-owned winery in the world reducing water use by 25% in the process.
If you have thought that it was all, you have never been so wrong. The capabilities of Watson seem infinite. It is also to revolutionize the financial sector with the IBM Watson Customer Insight for Banking. This device combines predictive and cognitive capabilities which enables dynamic behavioural segmentation to know better customers to create personalized sale offerings and marketing campaigns. Watson identify propensity to buy by determining the level of engagement for each customer based on their behaviours. Then it anticipates customer life event to provide a personalized experience. It even identifies “at risk” customers and highly profitable customers to aim those last ones more accurately. If newspapers often talk about the potential threats that represents artificial intelligence, they rarely talk about it as an enhancement of our human nature with all the improvements in the decision making and in the accuracy of our strategy that it allows. Yet, this is the reason why the finance is to deeply fund the development of AI, a form of awareness of how it will benefit from it.
Investments are to come thick and fast
With respect to this, numbers speak for themselves. According to the Tratica Institute, the AI market is going to be multiplied by almost 46, passing from 1.3 billion dollars in 2016 to 59.7 billion dollars in 2025. And who is investing in this market? According to the same institute, start-ups count for 24% of the total investment. The giant of the numeric (GAFAMI: Google, Apple, Facebook, Amazon, Microsoft, IBM) represent 76% of the total investment. It is relevant because those giants are focused on innovation, they embody new markets and they create new ones. So, their decisions are reliable. Also, because of their huge financial means, they create tendencies. Their strategies are to take control of a large range of IA technologies using their financial force to enrich their offer. They also want to face the disintermediation of user companies which develop their own AI solutions as Renault who do researches for autonomous vehicles when Google already pave the way for it. But investing in artificial intelligence is quite large. For this reason, the newspaper Le Monde has filed the fields of AI that are the most flourishing nowadays.
* The first one is the detection and the identification of objects (autonomous cars)
* The algorithmic commerce and trading (targeting of clients and financial trading)
* Localisation and cartography (navigation assistance)
* Predictive maintenance (anticipation of necessary repairs)
Even, with this segmentation, it is still hard to understand in what to invest to benefit of the AI soaring market. That is why it is interesting to focus on several other companies putting aside IBM and more widely the GAFAMI, and especially companies which are users of the improvement in the AI software as Watson or try to emancipate from it. Thus, companies as Quest Diagnostics which can thanks to IBM Watson work with the community oncologists which provides 70% of cares for cancer in the United States is one of these companies. It is listed on the NYSE with a market capitalisation of 13.52 billion dollars. But fashion companies as Marchesa can also become attractive. This last one has used Watson to create a cognitive dress shaped by admirers of the brand thanks to the data analysis of Watson.
What it is to remember is that companies as KPMG trusted in AI to verify and analyse data to provide better knowledges to its memberships, customers and checking comities. So, AI can be considered as a reliable sector technologically speaking and financially speaking. Even if Anglo-Saxons companies being a step forward, every country in Europe has its chance, as France with its academic excellence especially in mathematics and engineering. As demonstrated the settlement of the first European centre of R & D on AI by Facebook in France. However, during a debate on the BBC, the August 30th 1973, the mathematician sir James Lighthill had exposed its doubts on artificial intelligence during a session dedicated to it. The result is a brutal freeze of financing. It happened a “winter” on artificial intelligence which reminds us that the enthusiasm for this breakthrough could blow back as suddenly.
Artificial intelligence appears to be the next technological revolution which will reshape our society until extends we cannot even imagine. However, the clash of titans between Elon Musk and Mark Zuckerberg must raise our awareness upon an issue that could backfire against us. Because if someone as Elon Musk, one of the most innovative people of the century, ask authorities to regulate AI, even if Mark Zuckerberg find it irresponsible, it cannot be ignored. In my opinion, the solution is to invest in companies such as IBM and its 80 billion dollars revenue which are developing AI in order they have enough means to control their creation. To develop it the right way. We cannot swim against the tide because there are to many economic interests at stake, it comes under our responsibility as citizen to come with this disruption to make it succeed and not backfire against us.
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Written by Guilhem Garrel│ Independent Stock Analyst
Edited and Corrected
by Vee Venski
This article is not a promotion of financial investment. Investing money in financial instruments is risk-reward process. Losses and gains are part of financial investment process. Only invest money you can afford to lose.