In the news this week, the AI revolution is upon us, creating a tsunami of change that is sweeping through virtually every sector of the economy, but is the human brain-scale AI Supercomputer Is coming?
Welcome to The Digital Eye, your weekly roundup of the latest technology news.
Our team of experts have scoured the internet for the most exciting and informative articles so that you can stay up-to-date on all things digital, data, blockchain, AI & analytics.
This week’s the Top Reads:
- The Human Brain-Scale AI Supercomputer Is Coming
- HOW Ai can transform real-time verification of insurance
- Insurtech 2022 – the challenges and opportunities
- 3 Ways AI Will Change Your Job Forever
- TinyML is bringing neural networks to microcontrollers
Bonus Article:
- Blockchain and Machine Learning Combined for a Better Solution
We hope you find this information valuable and would appreciate your help in sharing it with others who may also be interested.
The Human Brain-Scale AI Supercomputer Is Coming
Are we ready?
👁️🗨️Read Article
“The AI revolution is upon us, creating a tsunami of change that is sweeping through virtually every sector of the economy, both public and private, and it’s having a profound impact on our daily lives already.
As computer scientist and venture capitalist, Kai-Fu Lee told CBS back in 2018: “I believe [AI] is going to change the world more than anything in the history of mankind. More than electricity.”
shared by @forbes
HOW Ai can transform real-time verification of insurance
Did you know there is 200,000+ Certificate of Insurance requests made daily in the US, & each certificate must be manually shared & reviewed
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“Artificial intelligence (AI) has taken a life of its own within the realm of insurance. With enhanced automation and analytic capabilities, the industry is able to take innovation and efficiency to new heights.”
shared by @InsuranceBizUS
Insurtech 2022 – the challenges and opportunities
“As technology costs reduce, more people will start adopting technology to improve their business.
👁️🗨️ Read Article
“The insurtech sector keeps surprising us year on year,” noted Andre Symes (pictured), co-CEO of the insurance software solutions provider Genasys in a recent IB Talk podcast. For while every year it is predicted that the bubble is going to slow down, in 2021 the sector broke numerous funding records – heading into 2022 having raised more than $10 billion in funding, up from $7 billion the year before. Therefore, it seems fair to say that the outlook is looking very optimistic for those people looking to use technology to improve the insurance world.”
shared by @InsuranceBizUK
3 Ways AI Will Change Your Job Forever
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Smart machines will augment and assist us
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AI will create new types of jobs
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AI probably won’t make you redundant – yet!
👁️🗨️ Read Article
“Artificial Intelligence – smart machines able to “learn” how to carry out tasks and become increasingly good at them – is everywhere in work today, and will only be more ubiquitous tomorrow.
In fact, Google’s CEO Sundar Pichai recently predicted that it will turn out to be the most profound human invention so far – more so than electricity, the internet, or even fire!”
shared by @Forbes
TinyML is bringing neural networks to microcontrollers
“TinyML makes it possible to run deep learning models on microcontrollers (MCU), which are much more resource-constrained”.
👁️🗨️ Read Article
“Deep learning models owe their initial success to large servers with large amounts of memory and clusters of GPUs. The promises of deep learning gave rise to an entire industry of cloud computing services for deep neural networks. Consequently, very large neural networks running on virtually unlimited cloud resources became very popular, especially among wealthy tech companies that can foot the bill.”
shared by @bdtechtalks
Bonus Article
Blockchain and Machine Learning Combined for a Better Solution
“Swarm Learning – data privacy-preserving framework that uses blockchain to decentralize machine learning-based systems.
👁️🗨️ Read Article
“Estimated figures show that one autonomous vehicle can generate terabytes of data per day. The data is used to train the machine learning model so the car can make timely decisions on the road.
Hospitals apply machine learning to identify diseases faster. These applications are critical, especially for highly contagious illnesses. The longer the patients don’t know the answer and therefore don’t isolate themselves properly, the riskier it is to transmit to others.”
The DiGITAL EYE