Tag: Artificial Intelligence

Humans are smarter than any type of AI – for now…

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Despite all the technological advancements, can machines today only achieve the first two of the thee AI objectives. AI capabilities are at least equalling and in most cases exceeding humans in capturing information and determining what is happening. When it comes to real understanding, machines still fall short – but for how long?

In the blog post, “Artificial Intelligence Capabilities”, we explored the three objectives of AI and its capabilities – to recap:

AI-8Capabilities

  • Capturing Information
    • 1. Image Recognition
    • 2. Speech Recognition
    • 3. Data Search
    • 4. Data Patterns
  • Determine what is happening
    • 5. Language Understanding
    • 6. Thought/Decision Process
    • 7. Prediction
  • Understand why it is happening
    • 8. Understanding

To execute these capabilities, AI are leaning heavily on three technology areas (enablers):

  • Data collecting devices i.e. mobile phones and IoT
  • Processing Power
  • Storage

AI rely on large amounts of data that requires storage and powerful processors to analyse data and calculate results through complex argorythms – resources that were very expensive until recent years. With technology enhancements in machine computing power following Moore’s law and the now mainstream availability of cloud computing & storage, in conjunction with the fact that there are more mobile phones on the planet than humans, really enabled AI to come to forefront of innovation.

AI_takes_over

AI at the forefront of Innovation – Here is some interesting facts to demonstrate this point:

  • Amazon uses machine learning systems to recommend products to customers on its e-commerce platform. AI help’s it determine which deals to offer and when, and influences many aspects of the business.
  • A PwC report estimates that AI will contribute $15.7 trillion to the global economy by 2030. AI will make products and services better, and it’s expected to boost GDP’S globally.
  • The self-driving car market is expected to be worth $127 billion worldwide by 2027. AI is at the heart of the technology to make this happen. NVIDIA created its own computer — the Drive PX Pegasus — specifically for driverless cars and powered by the company’s AI and GPUs. It starts shipping this year, and 25 automakers and tech companies have already placed orders.
  • Scientists believed that we are still years away from AI being able to win at the ancient game of Go, regarded as the most complex human game. Recently Google’s AI recently beat the world’s best Go player.

To date computer hardware followed a growth curve called Moore’s law, in which power and efficiency double every two years. Combine this with recent improvements in software algorithms and the growth is becoming more explosive. Some researchers expect artificial intelligence systems to be only one-tenth as smart as a human by 2035. Things may start to get a little awkward around 2060 when AI could start performing nearly all the tasks humans do — and doing them much better.

Using AI in your business

Artificial intelligence has so much potential across so many different industries, it can be hard for businesses, looking to profit from it, to know where to start.

By understanding the AI capabilities, this technology becomes more accessible to businesses who want to benefit from it. With this knowledge you can now take the next step:

  1. Knowing your business, identify the right AI capabilities to enhance and/or transform your business operations, products and/or services.
  2. Look at what AI vendors with a critical eye, understanding what AI capabilities are actually offered within their products.
  3. Understand the limitations of AI and be realistic if alternative solutions won’t be a better fit.

In a future post we’ll explore some real life examples of the AI capabilities in action.

 

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Artificial Intelligence Capabilities

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AI is one of the most popular talked about technologies today. For business, this technology introduces capabilities that innovative business and technology leadership can utilise to introduce new dimensions and abilities within service and product design and delivery.

Unfortunately, a lot of the real business value is locked up behind the terminology hype, inflated expectations and insecure warnings of machine control.

It is impossible to get the value from something that is not understood. So lets cut through the hype and focus to understand AI’s objectives and the key capabilities that this exciting technology enables.

There are many definitions of AI as discussed in the blog post “What is Artificial Intelligence: Definitions“.

Keeping it simple: “AI is using computers to do things that normally would have required human intelligence.” With this definition in mind, there are basically three things that AI is aiming to achieve.

3 AI Objectives

  • Capturing Information
  • Determine what is happening
  • Understand why it is happening

Lets use an example to demonstrate this…

As humans we are constantly gathering data through our senses which is converted by our brain into information which is interpreted for understanding and potential action. You can for example identify an object through site, turn it into information and identify the object instantly as, for example, a lion. In conjunction, additional data associated with the object at the present time, for example the lion is running after a person yelling for help, enables us to identify danger and to take immediate action…

For a machine, this process is very complex and requires large amounts of data, programming/training and processing power. Today, technology is so advanced that small computers like smart phones can capture a photo, identify a face and link it to a name. This is achieved not just through the power the smart phone but through the capabilities of AI, made available through services like facebook supported by an IT platform including, a fast internet connection, cloud computing power and storage.

To determine what is happening the machine might use Natural Language Understanding (NLU) to extract the words from a sound file and try to determine meaning or intent, hence working out that the person is running away from a lion and shouting for you to run away as well.

Why the lion is chasing and why the person is running away, is not known by the machine. Although the machine can capture information and determine what is happening, it does not understand why it is happening within full context – it is merely processing data. This reasoning ability, to bring understanding to a situation, is something that the human brain does very well.

Dispite all the technological advancements, can machines today only achieve the first two of the thee AI objectives. With this in mind, let’s explore the eight AI capabilities relevant and ready for use, today.

8 AI Capabilities

AI-8Capabilities

  • Capturing Information
    • 1. Image Recognition
    • 2. Speech Recognition
    • 3. Data Search
    • 4. Data Patterns
  • Determine what is happening
    • 5. Language Understanding
    • 6. Thought/Decision Process
    • 7. Prediction
  • Understand why it is happening
    • 8. Understanding

1. Image Recognition

This is the capability for a machine to identify/recognise an image. This is based on Machine Learning and requires millions of images to train the machine requiring lots of storage and fast processing power.

2. Speech Recognition

The machine takes a sound file and encodes it into text.

3. Search

The machine identifies words or sentences which are matched with relevant content within a large about of data. Once these word matches are found it can trigger further AI capabilities.

4. Patterns

Machines can process and spot patterns in large amounts of data which can be combinations of sound, image or text. This surpasses the capability of humans, literally seeing the woods from the trees.

5. Language Understanding

The AI capability to understand human language is called Natural Language Understanding or NLU.

6. Thought/Decision Processing

Knowledge Maps connects concepts (i.e. person, vehicle) with instances (i.e. John, BMW) and relationships (i.e. favourite vehicle). Varying different relationships by weight and/or probabilities of likelihood cn fine tune the system to make recommendations when interacted with. Knowledge Maps are not decision trees as the entry point of interaction can be at any point within the knowledge map as long as a clear goal has been defined (i.e. What is John’s favourite vehicle?)

7. Prediction

Predictive analytics is not a new concept and the AI prediction capability basically takes a view on historic data patterns and matches it with a new piece of data to predict a similar outcome based on the past.

8. Understanding

Falling under the third objective of AI – Understand what is happening, this capability is not currently commercially available.

To Conclude

In understanding the capabilities of AI you can now look beyond the hype, be realistic and identify which AI capabilities are right to enhance your business.

In a future blog post, we’ll examine some real live examples of how these AI capabilities can be used to bring business value.

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What is Artificial Intelligence: Definitions

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The term “Artificial Intelligence was first coined by John McCarthy in 1956. He is one of the “founding fathers” of artificial intelligence, together with Marvin Minsky, Allen Newell and Herbert A. Simon

Artificial Intelligence today is bathed in controversiality and hype mainly due to a misconception that is created by media. AI means different things to different people.  Some called it “cognitive computing”, others “machine intelligence”. It seems to be difficult to give a definition of what AI really is.

Different Definitions:

Wikipedia: “Artificial intelligence (AI, also machine intelligence, MI) is intelligence demonstrated by machines, in contrast to the natural intelligence (NI) displayed by humans and other animals. In computer science AI research is defined as the study of “intelligent agents“: any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals. Colloquially, the term “artificial intelligence” is applied when a machine mimics “cognitive” functions that humans associate with other human minds, such as “learning” and “problem solving”.

English Oxford Living Dictionary:  “The theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.”

Webster: ” A branch of computer science dealing with the simulation of intelligent behavior in computers. The capability of a machine to imitate intelligent human behavior.”

Google: “The theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision making, and translation between languages.”

Quartz: “Artificial intelligence is software or a computer program with a mechanism to learn. It then uses that knowledge to make a decision in a new situation, as humans do. The researchers building this software try to write code that can read images, text, video, or audio, and learn something from it. Once a machine has learned, that knowledge can be put to use elsewhere.”

Rainbird: “A computer doing a task that was previously thought would require a human.”

In my own words, keeping it simple: “AI is using computers to do things that normally would have required human intelligence.”

In other words, we might say that AI is the ability of computers/machines to use human knowledge modelled into algorithms and relational data, to learn from human reasoning and the associated conclusions/decisions, and use what has been learned to make decisions like a human would.

Thus can specialist (expensive) human knowledge be stored and processed, to make the decision making ability/application available to other non-specialist people (who do not have that specialised knowledge), empowering them to, through the use of the AI system, make a specialised decision.

Unlike humans, where specialists are numbered and constrained by human limitations, can AI-powered machines scale, don’t need to rest and they can process massively large volumes of information, can conduct tasks and make reasoning decisions at a significantly higher frequency and lower error ratio than humans, all at once!

Insightful Quotes on Artificial Intelligence

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Artificial Intelligence (AI) today, is a practical reality. It captivated the minds of geniuses and materialised through science fiction as I grew up. During the past 70 years (post WWII) AI has evolved from a philosophical theory to a game changing emerging technology, transforming the way digital enhances value in every aspect of our daily lives.

Great minds have been challenged with the opportunities and possibilities that AI offers.  Here are some things said on the AI subject to date. Within these quotes, the conundrum in people’s minds become clear – does AI open up endless possibilities or inevitable doom?

“I believe that at the end of the century the use of words and general educated opinion will have altered so much that one will be able to speak of machines thinking without expecting to be contradicted.”; Alan Turing (1950)

“It seems probable that once the machine thinking method has started, it would not take long to outstrip our feeble powers… They would be able to converse with each other to sharpen their wits. At some stage therefore, we should have to expect the machines to take control.”; Alan Turing

“The study is to proceed on the basis of the conjecture that every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it. An attempt will be made to find how to make machines use language, form abstractions and concepts, solve kinds of problems now reserved for humans, and improve themselves.”; John McCarthy (1956)

“AI scientists tried to program computers to act like humans without first understanding what intelligence is and what it means to understand. They left out the most important part of building intelligent machines, the intelligence … before we attempt to build intelligent machines we have to first understand how the brain things, and there is nothing artificial about that.”; Jeff Hawkins

“The question of whether a computer can think is no more interesting than the question of whether a submarine can swim.”; Edsger Dijkstra

“Whether we are based on carbon or on silicon makes no fundamental difference; we should each be treated with appropriate respect.”; Arthur Clarke (2010)

“…everything that civilisation has to offer is a product of human intelligence. We cannot predict what we might achieve when this intelligence is magnified by the tools that AI may provide, but the eradication of war, disease, and poverty would be high on anyone’s list. Success in creating AI would be the biggest event in human history.”; Stephen Hawking and colleagues wrote in an article in the Independent

“Why give a robot an order to obey orders—why aren’t the original orders enough? Why command a robot not to do harm—wouldn’t it be easier never to command it to do harm in the first place? Does the universe contain a mysterious force pulling entities toward malevolence, so that a positronic brain must be programmed to withstand it? Do intelligent beings inevitably develop an attitude problem? …Now that computers really have become smarter and more powerful, the anxiety has waned. Today’s ubiquitous, networked computers have an unprecedented ability to do mischief should they ever go to the bad. But the only mayhem comes from unpredictable chaos or from human malice in the form of viruses. We no longer worry about electronic serial killers or subversive silicon cabals because we are beginning to appreciate that malevolence—like vision, motor coordination, and common sense—does not come free with computation but has to be programmed in. …Aggression, like every other part of human behavior we take for granted, is a challenging engineering problem!”; Steven Pinker – How the Mind Works

“Ask not what AI is changing, ask what AI is not changing.”; Warwick Oliver Co-Founder at hut3.ai (2018)

“Sometimes at night I worry about TAMMY. I worry that she might get tired of it all. Tired of running at sixty-six terahertz, tired of all those processing cycles, every second of every hour of every day. I worry that one of these cycles she might just halt her own subroutine and commit software suicide. And then I would have to do an error report, and I don’t know how I would even begin to explain that to Microsoft.”; Charles Yu

“As more and more artificial intelligence is entering into the world, more and more emotional intelligence must enter into leadership.”; Amit Ray

“We’ve been seeing specialized AI in every aspect of our lives, from medicine and transportation to how electricity is distributed, and it promises to create a vastly more productive and efficient economy …”; Barrack Obama

“Artificial intelligence is the future, not only for Russian, but for all of humankind. It comes with colossal opportunities, but also threats that are difficult to predict. Whoever becomes the leader in this sphere will become the ruler of the world.”; Vladimir Putin

“I think we should be very careful about artificial intelligence. If I had to guess at what our biggest existential threat is, I’d probably say that. So we need to be very careful.”; Elon Musk

“Whenever I hear people saying AI is going to hurt people in the future I think, yeah, technology can generally always be used for good and bad and you need to be careful about how you build it … if you’re arguing against AI then you’re arguing against safer cars that aren’t going to have accidents, and you’re arguing against being able to better diagnose people when they’re sick.”; Mark Zuckerberg

“Most of human and animal learning is unsupervised learning. If intelligence was a cake, unsupervised learning would be the cake, supervised learning would be the icing on the cake, and reinforcement learning would be the cherry on the cake. We know how to make the icing and the cherry, but we don’t know how to make the cake. We need to solve the unsupervised learning problem before we can even think of getting to true AI.”; Yan Lecun

“Artificial intelligence would be the ultimate version of Google. The ultimate search engine that would understand everything on the web. It would understand exactly what you wanted and it would give you the right thing. We’re nowhere near doing that now. However, we can get incrementally closer to that, and that is basically what we’re working on.”; Larry Page,  Co-Founder at Google (2000)

“If you had all of the world’s information directly attached to your brain, or an artificial brain that was smarter than your brain, you’d be better off.” – Sergey Brin Co-Founder at Goolgle (2004)