The Brief

“Most people know Lyft as a rideshare company. Right? But, the truth of the matter is we are focused on improving people's lives with the world's best transportation”

Zach Greenberger

Head of Strategic Business Development & Supply Chain, Lyft 

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BY THE NUMBERS

The significance of combining human expertise with AI, machine learning, natural language processing, and pattern recognition to augment foresight across organisations.

What impact will it have on productivit y and ef f i c i e n cy by 2026? 85% How many enterprises will b e d o ing this? 25%

“Transformation is also about process transformation and then people transformation”

Abdul Manik

Chief Technology Innovation Officer, Randstad 

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“There's a recognition that AI is playing a bigger role in society. The technology has been around for decades”

Lee Tiedrich

Ethical Technology Professor, Duke University 

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Veriff: enabling trust with intelligent and automated IDV

Following the announcement that Veriff has joined the Amazon Web Services (AWS) Partner Network, we take a look at the work the company has done with AI

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LambdaTest launches a smart testing platform, HyperTest

LamdbaTest’s new cloud-based website and web app testing platform, HyperTest, is up to 70% faster than any other traditional test execution platform

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Nauto: Creating predictive vehicle safety technology

We take a look at Nauto, the enterprise AI company aiming to predict collisions before they occur and give drivers more reaction time with AI-powered sensors and alerts

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How important is natural language processing really?

Natural language processing (NLP) is so embedded into our daily lives we hardly notice it. When you use Alexa, you are conversing with an NLP machine and when you type into a chatbot NLP technology takes charge to support your query. The list of things this technology is used for is almost endless.

NLP market size

The NLP market is fast expanding. According to the research firm, MarketsandMarkets, the NLP market will grow to USD 35.1 billion by 2026 from 11.6 billion in 2020.

Adopting this technology with caution

Although it is clear that this technology is here to stay, and brings a significant amount of benefits to the organisations that embrace it, technologists need to make note of some drawbacks when adopting this technology. An important consideration for practitioners is the choice of natural language. Most models are good at the English language while performing below par in several other languages.

With this technology permeating throughout society, it is clear it is going nowhere any time soon and as it grows in magnitude and significance, considerations around language and efficiency need to be made.  DEEPMIND Following a successful 2021, DeepMind is now moving into the world of NLP with the creation of its AI algorithm that can perform a wide range of language tasks and claims to be better than any existing similar software.

 NVIDIA Leading graphics chip company NVIDIA has been named as a top AI stock to watch in 2022 since it has taken advantage of the AI boom. NVIDIA’s graphics cards could someday be supplanted by more specialised processors designed for AI.

 AI GOVERNANCE Technology experts predicted that 2021 would mark the year of AI governance. However, the Carnegie Council for Ethics in International Affairs stated that AI systems and algorithmic technologies are being embedded and scaled far more quickly than existing governance frameworks are evolving.

 TRUE ARTIFICIAL

INTELLIGENCE

Elwin Loomis, Head of Digital of Bremer Bank argued that our current artificial intelligence is not really intelligent. By terming the technology we have as ‘intelligent’, this creates a false narrative and underestimates the work needed to materialise the ‘real’ AI.