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:
- 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
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 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:
- Knowing your business, identify the right AI capabilities to enhance and/or transform your business operations, products and/or services.
- Look at what AI vendors with a critical eye, understanding what AI capabilities are actually offered within their products.
- 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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