Oct 28, 2020

Insurance groups caution government on AI road tech

AI
thatcham
ABI
cars
Paddy Smith
2 min
ALKS
Thatcham Research and the Association of British Insurers warn the UK government that Automated Lane Keeping Systems are not ready for introduction in 2...

Automated Lane Keeping Systems (ALKS) are not ready to be deployed in 2021, according to insurance lobbyists.

Thatcham Research, the motor insurers’ automotive research centre, and the Association of British Insurers (ABI) have warned the UK government that the technology, which aims to assist autonomous vehicles, is not mature enough to be introduced to roads early next year.

What is ALKS?

The government is expected to allow ALKS on British motorways from spring, subject to the findings of a safety consultation. It would legally allow a driver to remove their hands from the steering wheel and take their eyes off the road at speeds of up to 70mph.

Thatcham Research director of research Matthew Avery said, “Motorists could feasibly watch television in their car from early next year because they believe their Automated Lane Keeping System can be completely trusted to do the job of a human driver.

“But that’s not the reality. The limitations of the technology mean it should be classified as ‘assisted driving’ because the driver must be engaged, ready to take over.”

ALKS 'may not operate safely'

ABI general insurance policy director James Dalton said, “Vehicles equipped with an automated lane-keeping system are a great step towards developing automated vehicles.

“However, drivers must not be given unrealistic expectations about a system’s capability. Thatcham Research has identified some concerning scenarios where ALKS may not operate safely without the driver intervening.”

Researchers point to weaknesses regarding pedestrian encroachment, debris in the road, lane closures and human response times at the speeds involved.

Avery said: “Our conclusion is Automated Lane Keeping System technology is not safe enough to be classified as automated. We believe it should be regarded as assisted technology because the driver needs to remain alert.

“The Government’s proposed timeline for the introduction of automated technology must be revised. It simply isn’t safe enough and its introduction will put UK motorists’ lives at risk.”

Share article

Jun 22, 2021

What is neuromorphic AI?

Intel
neuromorphicai
AI
machinelearning
2 min
Neuromorphic computing – or neuromorphic AI – is the hardware side of artificial intelligence, changing the rules for the future of machine learning

AI is dead. Long live AI?

 

AI is evolving. The first generation of machine learning used ordinary logic and rules to draw conclusions in a very specific manner. A good example would be IBM’s Deep Blue computer, which was trained to play chess to championship standard. That hasn’t disappeared, but it has been augmented by more perceptive deep learning networks that can analyze a broader set of parameters and provide intelligent insights.

 

And neuromorphic AI is next?

 

Correct. Neuromorphic computing is a way of designing hardware – microprocessors, really – to work more like human brains. The idea is that this new iteration of AI hardware will allow machine learning of the future to deal better with ambiguity and contradiction, things that are currently difficult to process for computers.

 

How does neuromorphic AI work?

 

The problem with current chip architecture is that it is not very efficient. Because of the linearity of the process, the chips have to built with a massive amount of horsepower just in case it’s needed. Building a human brain that way would be unfeasible, so engineers have had to rethink the nature of chip design in their quest to get computers to perform more of the tasks human brains are good at. Enter SNNs.

 

What’s an SNN?

 

A spiking neural network (SNN) is, in the words of chipmaker Intel, “a novel model for arranging those elements to emulate natural neural networks that exist in biological brains.” Each ‘neuron’ fires independently, triggering other neurons only when they are required. Intel again: “By encoding information within the signals themselves and their timing, SNNs simulate natural learning processes by dynamically remapping the synapses between artificial neurons in response to stimuli.”

Share article