- This content is produced by The Australian Financial Review in commercial partnership with the Commonwealth Bank The Internet of Medical Things presents a range of new opportunities for medical businesses and entrepreneurs, claims Mark Dougan, Frost and Sullivan’s Consulting Director for Asia-Pacific.
- This was one of the business opportunities in the future Internet of Medical Things market – estimated to be worth $20 billion by the beginning of next decade – laid out by Mr Dougan for businesses in the healthcare sector at the recent Australian Healthcare Week conference in Sydney.
- In the very near future, wearable devices will be able to track every aspect of health and fitness and – when combined with artificial intelligence, robotics and the Internet of Medical Things – there are many opportunities for businesses and practitioners throughout the medical industry.
- Mr Dougan did warn that there are risks for businesses in the Internet of Medical Things, and cited six common points of failure — ranging from products beings too complex and not interoperable, through to misdirected business models.
- “How does your device or solution integrate primary and home-based care; who do you need to partner with; how effectively can you reach the end patient; what’s your business model; and finally, how can you as an organisation transform and disrupt how healthcare is delivered.”
The Internet of Medical Things presents a range of new opportunities for medical businesses and entrepreneurs.
Continue reading “Wearables and artificial intelligence define future”
- Machine learning is the science of getting computers to act without being explicitly programmed.
- In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome.
- From our friends at R2D3 is a very interesting visual introduction to machine learning.
Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving…
Continue reading “A Visual Introduction to Machine Learning”
- To prove this, the experimenters asked the doctors to teach a group software developers how to spot cancer in an MRI image.
- Of course, you could point out that doctors’ jobs could be put at risk by the rise of intelligent machines — and you would be right.
- In the future, we may discover that the best and highest value use for humans won’t be in doing repetitive tasks like driving trucks or “practicing” medicine, but in teaching machines how to do them so humans are freed up to innovate.
- Do a quick Google search and you will see a multitude of stories on how AI and intelligent machines are replacing human (educated) guesswork with super-human precision.
- So instead of worrying about the threat of Artificial Intelligence, let’s look forward to a more prosperous future created by the amazing things AI makes possible.
Learning to Love Artificial Intelligence
Continue reading “Learning to Love Artificial Intelligence”
- After the initial release, I got tons of great ideas from all of you, along with some very useful code submissions either in the comments or by a pull request on the Github page.
- This is a fantastic idea.
- If you have some ideas, submit a pull request on the Github Project Page or share a gist/text dump…etc.
- Another idea someone else had, which will be helpful for anyone who struggled with bad FPS before, or moving forward, was that you could use a game mod to slow down the in-game speed/time.
- This isn’t meant to be a GTA V mods tutorial, but I do want to bring your attention to these trainers, mainly because they make it super easy to create the wanted settings for our agent.
Python Programming tutorials from beginner to advanced on a massive variety of topics. All video and text tutorials are free.
Continue reading “Python Plays GTA V Part 8”
- Artificial Intelligence will Speak Its Own Language — SoonGrounded language is a new step towards Artificial Intelligence revealed by OpenAI.The article is about a system that invents a language which is tied to perception of the world.
- In sum, the post reveals possibilities that might be opened via researches related to an artificial language.
- At least the language will be similar to a signal language typical for animals.
- Further languages will be evolved into more complex technologies…This article was originally published on pionic.
The article is about a system that invents a language which is tied to perception of the world. In sum, the post reveals possibilities that might be opened via researches related to an artificial…
Continue reading “Artificial Intelligence will Speak Its Own Language — Soon”
- The blue line gives the actual house prices from historical data (Yactual)
The difference between Yactual and Ypred (given by the yellow dashed lines) is the prediction error (E)
So, we need to find a line with optimal values of a,b (called weights) that best fits the historical data by reducing the prediction error and improving prediction accuracy.
- So, our objective is to find optimal a, b that minimizes the error between actual and predicted values of house price:
This is where Gradient Descent comes into the picture.
- Gradient descent is an optimization algorithm that finds the optimal weights (a,b) that reduces prediction error.
- Lets now go step by step to understand the Gradient Descent algorithm:
Initialize the weights(a & b) with random values and calculate Error (SSE)
Calculate the gradient i.e. change in SSE when the weights (a & b) are changed by a very small value from their original randomly initialized value.
- Adjust the weights with the gradients to reach the optimal values where SSE is minimized
Use the new weights for prediction and to calculate the new SSE
Repeat steps 2 and 3 till further adjustments to weights doesn’t significantly reduce the Error
We will now go through each of the steps in detail (I worked out the steps in excel, which I have pasted below).
In Data Science, Gradient Descent is one of the important and difficult concepts. Here we explain this concept with an example, in a very simple way. Check this out.
Continue reading “Keep it simple! How to understand Gradient Descent algorithm”
- Image copyright
AlphaGo will challenge some of China’s top Go players later this month
Google has challenged China’s top Go player to a series of games against its artificial intelligence technology.It said the software would play a best-of-three match against Ke Jie, among other games against humans in the eastern Chinese city of Wuzhen from 23-27 May.Last year, the Google program recorded a 4-1 victory against one of South Korea’s top Go players.One expert said that result had come as a surprise.
- Image copyright
AlphaGo won four matches out of five against Lee Se-dol
Google’s AlphaGo software was developed by British computer company DeepMind, which was bought by the US search firm in 2014.
- Image copyright
Ke Jie – seen on the far right – met Google chief executive Sundar Pichai in Beijing last year
In addition to the games against Mr Ke, AlphaGo will also:
play games involving one Chinese pro facing off against another, each of whom will have an AlphaGo-powered virtual teammate
challenge a five-person team containing some of China’s top players, who will work together to try to beat the AI
Over the past year, DeepMind’s technology has also been used to find ways to reduce energy bills at Google’s data centres as well as to try to improve care in British hospitals.
- “If it loses this match, a lot of people will be delighted to claim that Google and DeepMind has overpromised and that this is the kind of hype we always get with AI,” commented Mr Chace.
- Media playback is unsupported on your device
Media captionA brief guide to Go
Go is thought to date back to several thousand years ago in China.Using black-and-white stones on a grid, players gain the upper hand by surrounding their opponent’s pieces with their own.The rules are simpler than those of chess, but a player typically has a choice of 200 moves, compared with about 20 in chess – there are more possible positions in Go than atoms in the universe, according to DeepMind’s team.That means a computer cannot win simply via brute force – searching through the consequences of millions of moves in seconds.It can be very difficult to determine who is winning, and many of the top human players rely on instinct.To prepare for its victory over Lee Se-dol, DeepMind trained its software on 30 million expert moves and then set the machine to play against itself millions of times to get a sense of what strategies worked.The result was that some of the innovative moves AlphaGo made in its landmark match were described as being “beautiful” and highly unusual by observers.
AlphaGo will soon challenge a Chinese teenager, recognised by many as the world’s top player.
Continue reading “Google’s AI seeks further Go glory”
- Just six companies mentioned AI in their earnings calls in the first quarter of 2013, according to data compiled by Bloomberg.
- And between the third and fourth quarters of 2016, the number of companies name-checking AI during earnings calls rose to 191 from 107.
- “We’re in a hype cycle,” Oren Etzioni, CEO of the AIlen Institute for Artificial Intelligence, told BuzzFeed News.
- Artificial intelligence is being mentioned on earnings calls by executives at companies with big AI research operations like Facebook and Alphabet.
- AI’s new role in earnings calls is largely aspirational, Etzioni argued, noting that artificial intelligence is not plug and play, and typically requires a good deal of labor to develop and implement.
AI is being name-checked during corporate earnings call at lot these days. Some say the enthusiastic chatter outpaces technical reality.
Continue reading “We’re In An Artificial Intelligence Hype Cycle”
- We know that artificial intelligence will soon reshape our world.
- But which companies will lead the way?
- To help answer that question, research firm CB Insights recently selected the “AI 100,” a list of the 100 most promising artificial intelligence startups globally.
- The private companies were chosen (from a pool of over 1,650 candidates) by CB Insights’ Mosaic algorithm, based on factors like financing history, investor quality, business category, and momentum.
- A look at the 50 largest startups on the list, ranked by total funds raised, shows that investment in AI is surging worldwide.
A look at the most promising global startups working with artificial intelligence.
Continue reading “50 Companies Leading the Artificial Intelligence Revolution”