- That could make for a 1+3 (quad-core) or 1+7 (octacore) layout, where each individual core has its own performance and power characteristics.
- The claim it’s making is that this setup can improve responsiveness for AI, with a 50x boost in AI performance over the next 3-5 years, and 10x between the (still Cortex-A9) CPU and specialized “accelerator hardware.”
ARM processor technology already powers many of the devices you use every day, and now the company is showing off its plans for the future with DynamIQ. Aimed s…
Continue reading “ARM’s latest CPUs are ready for an AI-powered future”
- ARM tipped its hand today with the announcement of DynamIQ, a new technology it says will lay the groundwork for its next generation of mobile processors.
- Like other mobile chip makers, the company’s got a lot to contend with when it comes to future-proofing its offerings, and certainly ARM’s making some pretty big claims for what it’s calling its “biggest micro-architectural shift since […] 2011”
Central to the company’s speed boasts are its focus on future artificial intelligence, an aspect of technology that will continue to grow more central to mobile computing over the next several years, both through the proliferation of smart-assistants, autonomous vehicles and beyond.
- As with offerings from other mobile chip makers, the company is targeting a wide range of different computing platforms that move well beyond mobile.
- Microsoft has already laid some of the groundwork for additional applications back in December when it announced that it would be bringing its apps to the company’s mobile processors, in an attempt to get hardware makers to build a wider variety of devices for the operating system.
- ARM’s not giving exact dates for the technology’s anticipated arrival, only stating that it expects its hardware partners to ship an additional 100 billion ARM-based chips by the year 2021, having shipped roughly half that number between 2013 and 2017.
ARM tipped its hand today with the announcement of DynamIQ, a new technology it says will lay the groundwork for its next generation of mobile processors…
Continue reading “ARM’s next-gen chip design puts the focus on artificial intelligence”
- Scientists at the Oxford University have claimed to develop a new computer software program that can lip-read better than humans, which might give the hearing impaired a helping hand.
- The new artificial intelligence (AI) software system called “Watch, Attend and Spell (WAS)” has been developed by Oxford University in collaboration with Google’s DeepMind.
- The AI system correctly lip-read 50 percent of silent speech, while professional lip-readers got only 12 percent right, researchers found.
- Speaking on the tech’s core value, Jesal Vishnuram, Action on Hearing Loss Technology Research Manager, said: “Action on Hearing Loss welcomes the development of new technology that helps people who are deaf or have a hearing loss to have better access to television through superior real-time subtitling.
- AI lip-reading technology would be able to enhance the accuracy and speed of speech-to-text especially in noisy environments and we encourage further research in this area and look forward to seeing new advances being made.”
Researchers develop an AI software system that lip-reads better Scientists at the Oxford University have claimed to develop a new computer software program
Continue reading “Researchers Build An AI That’s Better At Reading Lips Than Humans » TechWorm”
- In particular, neural layers, cost functions, optimizers, initialization schemes, activation functions, regularization schemes are all standalone modules that you can combine to create new models.
- The core data structure of Keras is a model, a way to organize layers.
- A core principle of Keras is to make things reasonably simple, while allowing the user to be fully in control when they need to (the ultimate control being the easy extensibility of the source code).
- You can now iterate on your training data in batches:
Alternatively, you can feed batches to your model manually:
Evaluate your performance in one line:
Or generate predictions on new data:
Building a question answering system, an image classification model, a Neural Turing Machine, or any other model is just as fast.
- For a more in-depth tutorial about Keras, you can check out:
In the examples folder of the repository, you will find more advanced models: question-answering with memory networks, text generation with stacked LSTMs, etc.
Keras is a high-level neural networks API, written in Python and capable of running on top of either TensorFlow or Theano. It was developed with a focus on enabling fast experimentation. Being able to go from idea to result with the least possible delay is key to doing good research.
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- In a nutshell, Distill is an interactive, visual journal for machine learning research.
- One day, perhaps, Distill articles will be a creative medium in their own right, a medium where it is possible to do exploratory machine learning research.
- At launch, Distill contains expository articles on subjects such as attention in neural networks, visualizing high-dimensional data using t-SNE, and using neural nets to generate handwriting.
- Going forward, Distill will publish both original research articles and expository articles.
- Distill articles will appear in Google Scholar, which will help authors receive academic credit.
The journal Distill launches today. In a nutshell, Distill is an interactive, visual journal for machine learning research. Going forward, Distill will publish both original research articles and expository articles. If you’re interested in submitting, please consult the page about publishing in Distill.
Continue reading “Distill: An Interactive, Visual Journal for Machine Learning Research – Y Combinator”
The web is a powerful medium to share new ways of thinking. Over the last few years we’ve seen many imaginative examples of such work. But traditional academic publishing remains focused on the PDF, which prevents this sort of communication.
Continue reading “Machine Learning Research Should Be Clear, Dynamic and Vivid. Distill Is Here to Help.”
- While robots and computers will probably never completely replace doctors and nurses, machine learning/deep learning and AI are transforming the healthcare industry, improving outcomes, and changing the way doctors think about providing care.
- Machine learning is improving diagnostics, predicting outcomes, and just beginning to scratch the surface of personalized care.
- This is an especially promising field into which to introduce machine learning because computers and deep learning algorithms are getting more and more adept at recognizing patterns — which, in truth, is what much of diagnostics is about.
- Lumiata has developed predictive analytics tools that can discover accurate insights and make predictions related to symptoms, diagnoses, procedures, and medications for individual patients or patient groups.
- The Care Trio team has developed a three-pronged approach that helps doctors devise and understand the best care protocols for cancer patients.
While robots and computers will probably never completely replace doctors and nurses, machine learning/deep learning and AI are transforming the healthcare industry, improving outcomes, and changing the way doctors think about providing care. Machine learning is improving diagnostics, predicting outcomes, and just beginning to scratch the surface of personalized care. Imagine walking […]
Continue reading “How Machine Learning, Big Data And AI Are Changing Healthcare Forever”