Talent is core to U.S. competitiveness in artificial intelligence, and international graduate students are a large source of AI talent for the United States. More than half of the AI workforce in the United States was born abroad, as were around two-thirds of current graduate students in AI-related fields. Tens of thousands of international students get AI-related degrees at U.S. universities every year. Retaining them, and ensuring a steady future talent inflow, is among the most important things the United States can do to address persistent domestic AI work-force shortages and to remain the global leader in AI.
… The good news is that student retention has historically been a core U.S. strength, with well over 80 percent of international U.S.-trained AI PhDs staying in the country, including those from AI competitors such as China.
…The bad news is that two trends are placing this U.S. strength in student retention at risk. Read More
Tag Archives: Training
These are the best free Artificial Intelligence educational (2020)
Deep learning is not a beginner-friendly subject — even for experienced software engineers and data scientists.
Deep learning is not a beginner-friendly subject — even for experienced software engineers and data scientists. If you’ve been Googling this subject, you may have been confused by the resources you’ve come across.
To find the best resources, we surveyed engineers on their favorite sources for deep learning, and these are what they recommended.
These educational resources include online courses, in-person courses, books, and videos. All are completely free and designed by leading professors, researchers, and industry professionals like Geoffrey Hinton, Yoshua Bengio, and Sebastian Thrun. Read More
Finland is making its online AI crash course free to the world
Last year, Finland launched a free online crash course in artificial intelligence with the aim of educating its citizens about the new technology. Now, as a Christmas present to the world, the European nation is making the six week program available for anyone to take.
Strictly speaking, it’s a present for the European Union. Finland is relinquishing the EU’s rotating presidency at the end of the year, and decided to translate its course into every EU language as a gift to citizens. But there aren’t any geographical restrictions as to who can take the course, so really it’s to the world’s benefit. Read More
Questioning The Long-Term Importance Of Big Data In AI
No asset is more prized in today’s digital economy than data. It has become widespread to the point of cliche to refer to data as “the new oil.” As one recent Economist headline put it, data is “the world’s most valuable resource.”
Data is so highly valued today because of the essential role it plays in powering machine learning and artificial intelligence solutions. Training an AI system to function effectively—from Netflix’s recommendation engine to Google’s self-driving cars—requires massive troves of data.
The result has been an obsession with bigger and bigger data. He with the most data can build the best AI, according to the prevailing wisdom. Read More
18 Best Artificial Intelligence Courses Online and Tutorial
Looking for Artificial Intelligence Tutorial to learn introduction to artificial intelligence? Grab the list of Best Artificial Intelligence Courses Online, Tutorials, and Training are offered by a number of massive open online course (MOOC) providers like Udemy, Coursera, and edX. Artificial Intelligence (AI) and machine intelligence are the most booming topics in every industry now. Read More
5 Simple Full Stack Data Science Projects To Put On Your Resume
Whether large or small, almost every organisation is looking for aspiring data scientists who will not only help them churn out meaningful insights from data but also help them stay ahead of the curve.
It does not matter if you are a college drop-out or a fresher, with the right knowledge of tools and a good understanding of the concepts of machine learning you can still pursue a fruitful data science career with a good pay scale. Read More
Faster Neural Network Training with Data Echoing
In the twilight of Moore’s law, GPUs and other specialized hardware accelerators have dramatically sped up neural network training. However, earlier stages of the training pipeline, such as disk I/O and data preprocessing, do not run on accelerators. As accelerators continue to improve, these earlier stages will increasingly become the bottleneck. In this paper, we introduce “data echoing,” which reduces the total computation used by earlier pipeline stages and speeds up training whenever computation upstream from accelerators dominates the training time. Data echoing reuses (or “echoes”) intermediate outputs from earlier pipeline stages in order to reclaim idle capacity. We investigate the behavior of different data echoing algorithms on various workloads, for various amounts of echoing, and for various batch sizes. We find that in all settings, at least one data echoing algorithm can match the baseline’s predictive performance using less upstream computation. In some cases, data echoing can even compensate for a 4x slower input pipeline. Read More
10 skills you'll need to survive the rise of automation
Automation is coming to the workplace.
Millions of jobs will be destroyed, but many jobs will also be simultaneously created in the process as well.
For those in the workforce – or for those just joining it for the first time – the big question is: what skills are needed to navigate this monumental shift in the economy? How will humans create value in an increasingly automated world? Read More
Webinar Wrap-up: How to Build a Career in AI and Machine Learning
Artificial Intelligence (AI) made headlines recently when people started reporting that Alexa was laughing unexpectedly. Those news reports led to the usual jokes about computers taking over the world, but there’s nothing funny about considering AI as a career field. Just the fact that five out of six Americans use AI services in one form or another every day proves that this is a viable career option. Read More
MIT’s AI can train neural networks faster than ever before — 20X Faster!
PROXYLESSNAS: DIRECTNEURALARCHITECTURESEARCH ONTARGETTASK ANDHARDWARE
Neural architecture search (NAS) has a great impact by automatically designing effective neural network architectures. However, the prohibitive computational demand of conventional NAS algorithms (e.g.104GPU hours) makes it difficult to directly search the architectures on large-scale tasks (e.g. ImageNet). Differentiable NAS can reduce the cost of GPU hours via a continuous representation of network architecture but suffers from the high GPU memory consumption issue(grow linearly w.r.t. candidate set size). As a result, they need to utilize proxy tasks, such as training on a smaller dataset, or learning with only a few blocks,or training just for a few epochs. These architectures optimized on proxy tasks are not guaranteed to be optimal on the target task. In this paper, we present ProxylessNAS that can directly learn the architectures for large-scale target tasks and target hardware platforms. We address the high memory consumption issue of differentiable NAS and reduce the computational cost (GPU hours and GPU memory) to the same level of regular training while still allowing a large candidate set. Experiments on CIFAR-10 and ImageNet demonstrate the effectiveness of directness and specialization. On CIFAR-10, our model achieves 2.08% test error with only 5.7M parameters, better than the previous state-of-the-art architecture AmoebaNet-B, while using 6×fewer parameters. On ImageNet, our model achieves 3.1% better top-1 accuracy than MobileNetV2, while being 1.2×faster with measured GPU latency. We also apply ProxylessNAS to specialize neural architectures for hardware with direct hardware metrics (e.g. latency) and provide insights for efficient CNN architecture design. Read More
Rick's Cafe AI 