- We’ll stick to playing rock-paper-scissors with AI, but all of this is leading to some serious visibility for AI as an emerging technology – which as investors make us want to get some skin in the game.
- The recent news that artificial intelligence (AI) startup Afiniti may have confidentially filed for IPO was the first time that we started to feel like this thing might be revving up for real now.
- It wasn’t just because this would be the first pure-play AI startup to see an IPO, it was because we really couldn’t believe how effective Afiniti’s technology was in adding value.
- Secondly we’re also seeing a very large number of AI startups getting into the game (over 1,500) which is the same sort of pile-on mentality we saw in the dot-com era.
- Now you just add a tagline to that same website that says “powered by AI” and now you’re an “AI company”.
If you’ve played Texas Hold’em, then you know how tough it is to be a good poker player. Lots of venture capitalists like to play poker, so it wasn’t surprising to see one who thought to himself “let’s see how good artificial intelligence (AI) really is“. He consulted a team of engineers and computer scientists to see where they might be able to exploit the AI agent named Lengpudashi. They then played 36,000 hands over 5 days and the AI agent kicked the isht out of them. We’ll stick to playing rock-paper-scissors with AI, but all of this is leading to some serious visibility for AI as an emerging technology – which as investors make us want to get some skin in the game. The problem is, there aren’t many ways to do that yet.
Continue reading “Is Artificial Intelligence the Next Dot-Com Bubble?”
- To discover the effect of electrical stimulation on memory, Michael Kahana and colleagues at the University of Pennsylvania turned to 150 volunteers who had previously had electrodes implanted in their brains to help control severe epilepsy.
- They then applied machine learning methods to this brain signal data, enabling them to predict if a person’s efforts to commit something to memory would later prove successful, based on the state of their brain at the time.
- They compared the effects of jolting someone during two different brain states – the pattern of signals linked to being likely to later remember something, and the pattern linked to being more likely to have a memory lapse.
- They found that giving electrical stimulation when a person’s brain signals suggested they would later forget the current item made that person 13 per cent more likely to recall it.
- So far, many studies have conflicted with each other on the effects of deep brain stimulation and recall.
Jolting the brain with electricity really does seem to boost memory, but only if it’s done at the right time. Now we can detect when the brain could use a shock
Continue reading “Machine learning shows exactly when to zap brain to boost memory”
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- To enable cookies, follow the instructions for your browser below.
- There is a specific issue with the Facebook in-app browser intermittently making requests to websites without cookies that had previously been set.
- This appears to be a defect in the browser which should be addressed soon.
- The simplest approach to avoid this problem is to continue to use the Facebook app but not use the in-app browser.
It was my blessing and my curse to be the world chess champion when computers finally reached a world championship level of play. When I resigned the final match game against the IBM supercomputer Deep Blue on May 11, 1997, I became the first world champion to be defeated in a classical match by a machine.
Continue reading “Rise of artificial intelligence: learning to love machines”
- Russia has made a humanoid robot which can shoot a handgun from each arm.
- Russia will also use the robot to fly a new unmanned spacecraft.
Russia makes gun shooting terminator like robot but claim it will not be terminator
Continue reading “Russia has Gun shooting Terminator Robot but denies they are building a Terminator”
- It’s not surprising as conversations are at the heart of unlocking opportunities such as a new job, business lead or career advice.
- That’s why we’re rolling out an even smarter messaging experience with the ability to message a connection from wherever you may be on LinkedIn, along with suggestions that can help connect you to a new job.
- For example, you can have a conversation with a connection without ever leaving their profile, or reach out to someone directly from the LinkedIn Feed.
- In fact, nearly 50% of LinkedIn members have found a job through a mutual connection.
- For example, when looking at a job posting at a company you’re interested in we’ll show you which of your connections work there, or who can introduce you to someone at the company.
Did you know that 80% of LinkedIn members consider professional networking to be important to career success? It’s not surprising as conversations are at the heart of unlocking opportunities such as a new job, business lead or career advice.
Continue reading “Introducing a Smarter Way to Message and Build Meaningful Relationships on LinkedIn”
- Caffe2 is a deep learning framework enabling simple and flexible deep learning.
- Built on the original Caffe, Caffe2 is designed with expression, speed, and modularity in mind, allowing for a more flexible way to organize computation.
- Caffe2 aims to provide an easy and straightforward way for you to experiment with deep learning by leveraging community contributions of new models and algorithms.
- Caffe2 comes with native Python and C++ APIs that work interchangeably so you can prototype quickly now, and easily optimize later.
- Caffe2 is accelerated with the latest NVIDIA Pascal™ GPUs and scales across multiple GPUs within a single node.
Run deep learning training with Caffe2 up to 3x faster on the latest NVIDIA Pascal GPUs.
Continue reading “Caffe2 Learning Framework and GPU Acceleration”
- We are excited to announce that the AWS Deep Learning AMI for Ubuntu now supports the newly launched Caffe2 project led by Facebook.
- The Deep Learning AMI v1.3_Apr2017 for Ubuntu provides a stable, secure, and high-performance execution environment for deep learning applications running on Amazon EC2.
- The AWS Deep Learning AMI (available for Amazon Linux and Ubuntu) and the AWS Deep Learning CloudFormation Template let you quickly deploy and run any of the major deep learning frameworks at any scale.
- The AWS Deep Learning AMI is provided and supported by Amazon Web Services, for use on Amazon EC2.
- There is no additional charge for the AWS Deep Learning AMI – you only pay for the AWS resources needed to store and run your applications.
We are excited to announce that the AWS Deep Learning AMI for Ubuntu now supports the newly launched Caffe2 project led by Facebook. AWS is the best and most open place for developers to run deep learning, and the addition of Caffe2 adds yet another choice. To learn more about Caffe2, check out the the Caffe2 developer site or the GitHub repository.
Continue reading “Deep Learning AMI for Ubuntu v1.3_Apr2017 Now Supports Caffe2”