James Kobielus
Contributor
James Kobielus is principal analyst at Franconia Research.
How Nvidia’s Arm acquisition will drive AI to every edge
Filling a gap in their offerings, Nvidia hopes to gain money and market share with Arm's extensive reach
Using robotics and immersive technologies to support work-from-home employees
The COVID-19 crisis has accelerated the long-term shift toward remote working as a standard business practice
Big tech faces intense political pressure in an election year
The sound and fury of recent congressional hearings are unlikely to result in regulatory action
Is the carbon footprint of AI too big?
Artificial intelligence obviously requires electricity and computers to work its practical magic. But don’t ignore the downstream environmental benefits
The sweet spot for robotic process automation in the COVID-19 response
RPA can smooth some of the bumps of working from home, but don’t expect it to solve everything
Social engineering hacks weaken cybersecurity during the pandemic
Disinformation, malware, and an array of cyberattacks are rising as fast as case counts
Which tech companies will survive the pandemic-triggered recession?
Bouncing back from a COVID-19 downturn depends on how well a company weathers the structural and frictional challenges. Hint: You'll need disruption and a healthy supply of cash
Quantum AI is still years from enterprise prime time
Quantum computing’s greatest potential for widespread adoption during this decade is in artificial intelligence
How data analysis, AI, and IoT will shape the post-pandemic ‘new normal’
Only a common public health infrastructure of AI, cloud computing, streaming, and the Internet of Things can marshal our data against pandemics
GPipe and PipeDream: Scaling AI training in every direction
New frameworks Google GPipe and Microsoft PipeDream join Uber Horovod in distributed training for deep learning
Coding together apart: Software development after COVID-19
Distance collaboration may become standard practice, aided by group collaboration tools
TensorFlow deepens its advantages in the AI modeling wars
Despite complaints about its complexity, TensorFlow supports every AI development, training, and deployment scenario you can imagine
AI companies plant the seeds for quantum machine learning
Quantum computing promises to accelerate analytics faster than the speed of light, but it still feels slightly unreal, in spite of the first signs of broad commercialization
Boosting AI’s smarts in the absence of training data
Zero-shot learning repurposes knowledge through statistical or semantic approaches without needing huge amounts of fresh training data
Keeping your enterprise AI expertise up to speed
AI is such a significant force, you can’t afford not to stay on top of the ever-changing developments
Making AI’s arcane neural networks accessible
Data scientists remain in hot demand, but they will give up more of their core functions this year and beyond to automated tools
Mitigating the risks of the AI black box
If we don’t understand how machine learning works, how can we trust it? Increasing model transparency creates risks as well as rewards
Artificial intelligence predictions for 2020
Machine learning applications, tools, techniques, platforms, and standards will see big changes in the next year
Boutique clouds rise on multicloud and microservices
Hoping to avoid cloud vendor lock-in, enterprises are moving workloads to niche providers