These industry applications can be similar to the Industrial Internet of Things (IIoT). Take underground mining, for instance, with its remote control and driverless equipment functions and the need to gather insights on predictive maintenance and energy management. Computers in these conditions must operate reliably under vibration, shock, and hot temperatures.

Seventy-five percent of data is forecasted to process outside the cloud by 2025, according to Gartner. Organizations need features in their servers such as higher performance, less data latency, and remote manageability.

Alongside withstanding extreme conditions, ruggedized edge platforms require various other functionality. The platforms need to perform real-time processing through an array of performance accelerators, offer sufficient storage capacity, and have rich I/O ports to be compatible with new and legacy machines. 

In collaboration with Arrow, Dell’s PowerEdge XR11 and XR12 servers aim to offer enterprise compute capabilities in the harshest edge environments. On the performance side, the XR12 is the more expandable of the two, coming across in its third-generation Intel Xeon scalable processors and GPU options, with support for up to two NVIDIA T4 cards or two of the A100, A10, or A40 GPUs, and flexible I/O choices. Storage for the XR11 and XR12 includes the Intel Optane Persistent Memory 200 series. At 16 inches, the chassis can maintain performance while being less than half the depth of a standard server. 

“The servers help OEM customers address the edge computing challenges faced outside the data center,” Dell notes. “Businesses can move workloads to the network edge and run AI algorithms to analyze and act on data near where it’s generated, reducing latency and providing quicker access to data for real-time decision making, saving time and money.”

By bringing computing power to the edge, innovative enterprises realize that a mix of centralized cloud and distributed edge environments are essential. Meanwhile, innovative vendors can now get data center-class performance right where the action is for their customers’ increasing edge deployments. Arrow can provide customized Dell solutions for enterprises that wish to take the next step, going through the entire lifecycle, from ideation development, prototyping, manufacturing, and global distribution.

The post The need for ruggedised edge: Bringing data centre-class performance closer to your data appeared first on AI News.

AI plays a key role in making what BMC Software calls an ADE (Autonomous Digital Enterprise). These cutting-edge businesses know how to wield the latest technologies to minimise manual tasks and maximise the use of uniquely human talents.

AI News joined Ram Chakravarti, CTO of BMC Software, to discuss autonomous digital enterprises and the growing demand for AIOps.

AI News: BMC coined the phrase “Autonomous Digital Enterprise” (ADE). What makes an ADE and what competitive benefits does it present?

Ram Chakravarti: An Autonomous Digital Enterprise (ADE) is made up of intelligent, interconnected, tech-enabled, value-creating systems that minimise manual effort to capitalise on human creativity, skills, and intellect across the enterprise. Transitioning to an ADE presents a variety of benefits for organisations, enabling them to rapidly evolve, and ultimately stay competitive through streamlined agility, customer centricity, and actionable insights. 

One of the key benefits is automation, working as a business function alongside humans, to execute tasks faster and reduce the risk of errors. This means that employees are no longer burdened with manual tasks and can focus on higher-value activities. In addition, an ADE optimises costs, while significantly enhancing customer satisfaction. To support the evolution to an ADE, organisations need to embrace new approaches to talent management, evolve IT departments and optimise technology buying.

AN: Why do we need AIOps and what are its benefits?

RC: There are numerous benefits that come with implementing AIOps. For starters, AIOps provides organisations with insights into all layers of the IT environment. Monitoring and maintaining large complex systems is becoming too much for humans alone. As an example, the volume of operational metrics and log data being created is overwhelming, which can drastically slow repair times when a problem does arise. By applying machine learning techniques and training the models using historical data, AIOps can analyse reams of performance data to identify potential issues, allowing IT teams to take precautionary maintenance measures before a problem impacts customers. An intelligent AIOps solution essentially automates manual processes, meaning organisations will begin to see an increase in employee satisfaction, productivity and customer retention, while significantly saving time and resources.

AN: Around a decade ago, DevOps was a new and barely understood term that has since become somewhat critical to success. Do you think we’ll look back on AIOps in the same way by the end of this decade?

RC: By the end of the decade, we can expect to see the demand for AIOps continue to grow as intelligent automation is added to the mix to help fix problems without human involvement, which I refer to as actionability. Additionally, the intelligence and predictive analytics capabilities of AIOps can be applied beyond traditional IT data: Consider operational data that’s generated by wind turbines, cell towers, trucking fleets. All of that data can be analysed to help predict physical failures and improve maintenance schedules. Noisy datasets will be a barrier of the past as smarter strategies and centralised AIOps solutions help organisations improve the customer experience, deliver on modern application assurance and optimisation, and coupled with intelligent automation to help organisations thrive as ADEs.

AN: What data can be obtained from sources like IoT devices, customer engagement systems, and social media, and how can such huge amounts of data be converted into actionable insights?

RC: By 2025, we can expect data to be reaching unprecedented levels, meaning essentially every company will become a technology-driven business. As noted above, industrial IoT can be used for predictive maintenance and improve monitoring of physical systems. Customer engagement and social media data are all part of delivering a transcendent customer experience. The ability to quickly aggregate, scrub, and analyse your data is key. It paves the way for differentiated business data with key insights across your technology, tools, and employees which then make it possible to deliver a powerful, personalised customer experience.

AN: BMC is a sponsor of this year’s AI and Big Data Expo Global in London and will also be hosting a keynote at the event. What insights do you plan on sharing with the audience?

RC: At the AI and Big Data Expo our focus will be on how enterprises are continuing to amass data at exponential rates, why it’s becoming more imperative to unlock its value and how traditional approaches to data and analytics transformations have seen high failure rates. In my session, I look forward to sharing a recipe for success that rapidly turns new insights into fully operationalised production deliverables – all designed to unlock tangible business value from data.

(Photo by Bill Oxford on Unsplash)

Ram Chakravarti will be sharing his invaluable insights during a keynote on day two of AI and Big Data Expo Global, which runs from 6-7 September 2021. Find out more about the event and how to attend here.

The post Ram Chakravarti, CTO, BMC Software: On the benefits of AIOps and autonomous digital enterprises appeared first on AI News.

The local government area is located in Victoria, Australia, and has an area of 37 square kilometers and a population of around 183,756. Illegal waste dumping in the city is a problem that causes both hygiene and safety problems.

Using Nokia’s Scene Analytics AI technology, the city hopes to gain a deeper understanding of waste disposal behaviour across the area.

Rob Mccabe, Head of Enterprise of Australia and New Zealand at Nokia, said:

“The City of Melbourne is using robust AI technology to offer its citizens, visitors, and businesses a greener and more liveable community.

In helping the City of Melbourne monitor and enhance services with real-time driven actions, Nokia Scene Analytics is supporting the safety, security and operational continuity of this city in a proactive and automated way.”

An existing network of cameras is being used as IoT sensors to monitor waste compactors. Nokia’s AI is used to filter and collate data from the cameras – combining it with other data, including from the compactor itself – to create real-time alerts and produce reports.

Lord Mayor Sally Capp, City of Melbourne, commented:

“This is a great example of using new technology to help remove illegal waste more quickly, make our city cleaner, and protect the environment.

Our partnership with Nokia is another way we are gathering data to make Melbourne a safer, smarter, and more sustainable city.

This innovative project will help to avoid hazards and make our streets even cleaner by allowing our waste services to better understand behavior trends related to the illegal and dangerous dumping of waste.”  

A virtual “tripwire” allows for real-time monitoring of compactors. Object detection and counting were used to determine the items being placed in the compactor and their impact on it. This data can be used to help predict when compactors may require maintenance in order to minimise downtime.

During the trial, all faces and license plates were blurred to maintain the privacy of individuals.

(Image Credit: City of Melbourne)

Find out more about Digital Transformation Week North America, taking place on November 9-10 2021, a virtual event and conference exploring advanced DTX strategies for a ‘digital everything’ world.

The post City of Melbourne trials Nokia’s AI tech to keep streets clean and safe appeared first on AI News.

Fetch.ai has caught the attention of investors for its potentially groundbreaking machine learning network of autonomous “agents” that can perform real-world tasks. It’s also caught our attention, making our list of innovative companies to watch in 2021.

IOTA was among the most hyped projects during the 2017 cryptocurrency/blockchain frenzy (or bubble, dependent on your perspective.) While most projects have since collapsed, IOTA continues to go from strength-to-strength and has announced a series of partnerships with giants like Dell and Jaguar Land Rover.

One partnership that both companies have in common is Bosch.

IOTA was the first to establish a partnership with Bosch when it announced that it was integrating with IOTA’s Data Marketplace. Last February, Fetch.ai announced its own partnership with Bosch as part of a joint project called the Economy of Things (EoT).

No specific project involving Fetch.ai, IOTA, and Bosch has been announced but it wouldn’t be surprising to see the first real-world adoption coming from the three companies.

While we can speculate on the exciting future possibilities, what’s actually been announced today is an agreement between Fetch.ai and IOTA to deliver a controlled data sharing environment for IoT devices and infrastructures. The ultimate goal is to enable the automated fee-less retrieval and private sharing of data.

Humayun Sheikh, CEO of Fetch.ai, said:

“The fundamental goal of this collaboration is to enable granular control over data and to reduce the reliance on centralised systems that take advantage of data.

While there are numerous partnerships focusing on data privacy, this one adds the layer of economic benefit for stakeholders via autonomous economic agents without compromising data privacy.

Enabling these agents to perform “useful economic work” on behalf of individuals, businesses, companies, and other entities or organizations will speed up the adoption of Fetch.ai autonomous economic agents and IOTA Streams thereby allowing them to communicate with sophistication across industries like mobility, supply chain, IoT and more.”

Holger Koether, Director of Partner Management at IOTA Foundation, added:

“The main feature of this partnership is offering a serious AI application for the devices that make up the machine economy on the IOTA and Fetch networks.

We are enabling data producers to take control over who can access the data they produce whether from a mobile device, environment IoT sensor, connected vehicle, Industrial IoT solution, and a host of IoT-focused use cases.

With this partnership, we hope both the Fetch and IOTA communities expand the functionally of what devices can do autonomously on distributed networks.”

IOTA has faced various criticisms over the years but the project now seems to have overcome most of its problems. The one major lingering criticism is of centralisation due to its ‘Coordinator’ node. However, that is set for removal in IOTA 2.0.

The IOTA 2.0 ‘Nectar’ devnet went live last week. For the first time, assets on the network will be persistent even after upgrades.

“IOTA 2.0 DevNet ‘Nectar’ marks a major milestone on IOTA’s trajectory towards full decentralisation,” commented Dominik Schiener, Co-Founder and Chairman of the IOTA Foundation. “I cannot understate the importance of this release: Nectar is the living proof that you can have feeless, scalable, secure, resource-efficient, and fully decentralised DLT. It’s a game-changer.”

With IOTA 2.0 heading towards its first release candidate later this year, we can expect many more announcements in the months to come.

Want to learn more from executives at the heart of this space? The Blockchain IoT Solutions Congress on March 8 2022 will explore the convergence of these two technologies and the use cases and industries that will benefit.

The post Fetch.ai announces partnership with IoT-focused distributed ledger IOTA appeared first on AI News.

Faethm’s mission is to prepare the world “for the future of work” by using an AI engine – trained on billions of workforce data points – to predict what jobs need reskilling versus upskilling.

James McLeod, VP of the EMEA region at Faethm, said

“Employers and employees alike need to change their perspective. The future of work is already here and the introduction of technology does not affect work in a uniform way.

We must acknowledge where it supplements existing work and invest in a targeted reskilling approach that recognises the new roles technology is creating and ensures human and machine labour complement one another.

Doing so will not only help businesses add capacity and increase productivity, but also ensure they are looking after employees—making financially beneficial and morally responsible decisions and creating a digitally-adept workforce for the future.”

In its latest UK Workforce Forecast report (registration required), Faethm expects 4.8 percent of work – equivalent to 1.4 million full-time roles – to be automated over the next 12 months. A further 2.9 percent is predicted to be augmented by AI.

Adjusted for population, Wales (5.3%), Northern Ireland (5.2%), and the North of England (5.1%) have the highest proportions of jobs at risk of automation.

Nan Craig, Data Analyst at Faethm, commented:

“Even ordinary downturns tend to increase automation, as companies are tempted to replace expensive labour with cheaper automated systems. However, the new conditions created by COVID-19 – and the need to reduce human interaction in public places – are making automation more attractive than in an ordinary recession. 

In-person human labour is becoming more expensive, due to safety considerations around space, PPE, and the ability to take time off to self-isolate, whereas machines and automated systems, in comparison, can be added without increasing infection risks, at a comparatively lower cost.

Longer-term changes in consumer behaviour could make a difference too, as more interactions shift online, meaning businesses are more likely to be considering automation than without the COVID-19 crisis.”

Jobs in the wholesale, retail, and financial sectors are most at-risk. These sectors represent nine percent of the workforce – around five million people – and Faethm estimates that the equivalent of 932,000 full-time roles in these sectors could be automated.

Faethm’s research finds that many staple UK jobs are at risk from automation and may cease to exist in the future. However, around 382,000 jobs could be created by the introduction of new technologies.

As the country rebuilds from the pandemic, Faethm wants to see a focus on where AI can augment human jobs rather than replace them. Automation can handle more of the routine, mundane, and less enjoyable daily tasks while humans can focus on areas machines struggle with such as creativity, compassion, and interpersonal skills.

(Photo by Lyman Gerona on Unsplash)

Interested in hearing industry leaders discuss subjects like this? Attend the co-located 5G Expo, IoT Tech Expo, Blockchain Expo, AI & Big Data Expo, and Cyber Security & Cloud Expo World Series with upcoming events in Silicon Valley, London, and Amsterdam.

The post Research finds 1.4 million UK jobs could be automated this year appeared first on AI News.

The global engineering giant will test key features of Fetch.ai’s testnet until the end of this month and will deploy a node on the network. The strategic engineering project between Fetch.ai and Bosch is called the Economy of Things (EoT).

Dr Alexander Poddey, the leading researcher for digital socio-economy, cryptology, and artificial intelligence in the EoT project, said:

“Our collaboration with Fetch.ai spans from the aspects of governance and orchestration of DLT-based ecosystems, multi-agent technologies to collective learning.

They share our belief that these elements are crucial to realising the economic, social, and environmental benefits of IoT technologies.”

Fetch.ai’s testnet launched in October 2020 and the firm is now gearing up for its mainnet launch in March. The company has been ramping up announcements in advance of the mainnet launch and just last week announced a partnership with FESTO to launch a decentralised marketplace for manufacturing.

After the mainnet launch, Bosch intends to run nodes and applications on Fetch.ai’s blockchain network.

Jonathan Ward, CTO of Fetch.ai, commented:

“We have been working with Bosch for some time towards our shared vision of building open, fair, and transparent digital ecosystems. I’m delighted to be able to announce the first public step in bringing these technologies into the real world.

We’re looking forward to working further with Bosch to bring about the wide adoption of these ground-breaking innovations, which will hugely benefit consumers and businesses in many industries including automotive, manufacturing, and healthcare.” 

Fetch.ai is working on decentralised autonomous “agents” which perform real-world tasks. 

Bosch is attracted to Fetch.ai’s vision of collective learning technologies and believes it can be a key enabler in their plans for AI-enabled devices—allowing AI agents to be trained which operate within smart devices while preserving users’ privacy and control of their data.

Fetch.ai’s vision is bold but it has the team and partnerships to pull it off. The company’s roster features talent with experience from DeepMind, Siemens, Sony, and a number of esteemed academic institutions.

Bosch has long expressed a keen interest in distributed ledger technologies and established multiple industry partnerships.

The venture capital arm of Bosch, Robert Bosch Venture-Capital, invested in the IOTA Foundation. Bosch later patented an IOTA-based digital payments system and recently financially supported a hackathon for the DLT platform which uses a scalable DAG (Directed Acyclic Graph) data structure called the ‘Tangle’ in a bid to overcome some of the historic problems with early blockchains.

Fetch.ai and IOTA are in the same space but have different goals, it’s not a choice of one or the other. Companies like Bosch can take advantage of the exciting potential offered by both DLTs to gain a competitive edge.

(Photo by Adi Goldstein on Unsplash)

Interested in hearing industry leaders discuss subjects like this? Attend the co-located 5G Expo, IoT Tech Expo, Blockchain Expo, AI & Big Data Expo, and Cyber Security & Cloud Expo World Series with upcoming events in Silicon Valley, London, and Amsterdam.

The post Bosch partners with Fetch.ai to ‘transform’ digital ecosystems using DLTs appeared first on AI News.

Even as a Brit, it can often feel like a translation app is needed between Bristolian, Geordie, Mancunian, Brummie, Scottish, Irish, or any of the other regional dialects in the country. For a geographically small country, we’re a diverse bunch – and US-made voice assistants often struggle with even the slightest accent.

The BBC thinks it can do a better job than the incumbents and first announced its plans to build a voice assistant called ‘Beeb’ in August last year.

Beeb is being trained using the BBC’s staff from around the country. As a public service, the institution aims to offer as wide representation as possible which is reflected in its employees.

The broadcaster also believes that Beeb addresses public concerns about voice assistants; primarily that they collect vast amounts of data for commercial purposes. As a taxpayer-funded service, the BBC does not rely on things like advertising.

“People know and trust the BBC,” a spokesperson told The Guardian last year, “so it will use its role as public service innovator in technology to ensure everyone – not just the tech-elite – can benefit from accessing content and new experiences in this new way.”

An early version of Beeb is now available for testing by UK participants of the Windows Insider program. Microsoft is heavily involved in the Beeb assistant as the company’s Azure AI services are being used by the BBC.

The first version of Beeb allows users to do virtual assistant norms like getting weather updates and the news, access radio and podcasts, and even grab a few jokes from BBC Comedy writers and facts from QI host Sandi Toksvig.

According to the broadcaster, Beeb won’t launch on dedicated hardware but instead will be designed to eventually be implemented in smart speakers, TVs, and mobiles.

While it still has a long way to go to take on the capabilities of Google, Alexa, Siri, and others, Beeb may offer a compelling alternative for accent-heavy Brits that struggle with American voice assistants.

Grab the Beeb app from the Microsoft Store here.

Interested in hearing industry leaders discuss subjects like this? Attend the co-located 5G Expo, IoT Tech Expo, Blockchain Expo, AI & Big Data Expo, and Cyber Security & Cloud Expo World Series with upcoming events in Silicon Valley, London, and Amsterdam.

The post The BBC’s virtual assistant is now available for testing in the UK appeared first on AI News.

The bill, passed on Wednesday, aims to accelerate the sweeping change of regulations across various fields to support the creation of such futuristic cities.

Addressing issues such as depopulation and an aging society will be the focus of the super cities. Technologies including big data and AI will be key to successfully tackling the challenging problems.

Large amounts of data will be collected and organised from across administrative organisations.

Local governments will be selected for the ambitious projects which will launch forums with the national government and private companies to take forward the plans.

Draft plans will be created from this deep public-private collaboration that will subsequently be submitted to the state government if approved by local residents.

As with many smart city plans, there are deep concerns about the collection of personal data and what it could mean for individual privacy. Local residents are sure to want assurance that any data collection is anonymous.

A similar bill was submitted to the Diet (Japan’s decision-making institution) last year. The bill was scrapped following calls from the ruling government to review it.

The revised bill was passed on Wednesday. Given the appetite for the project across the government; the plans are now expected to progress swiftly.

(Photo by Jezael Melgoza on Unsplash)

Interested in hearing industry leaders discuss subjects like this? Attend the co-located 5G Expo, IoT Tech Expo, Blockchain Expo, AI & Big Data Expo, and Cyber Security & Cloud Expo World Series with upcoming events in Silicon Valley, London, and Amsterdam.

The post Japan passes bill to build AI-powered ‘super cities’ addressing societal issues appeared first on AI News.

Chang played a major role in this year’s AI & Big Data Expo in Santa Clara last week, taking part in both a solo presentation on “Process Automation from IoT Data” and a panel discussion on “Data and the Customer”.

Following the event, AI News decided to catch up with Chang to discuss LG’s current experience in artificial intelligence and where the industry is heading next.

How important is AI becoming to differentiate from competing products?

With artificial intelligence gaining traction across a range of industries, it’s becoming important to allow differentiation among competing products. LG’s pursuit of “Evolve, Connect, Open” when it comes to AI and ThinQ offers enhanced convenience for users with diverse needs and tech preferences in their homes through personalised, proactive, easy, and efficient solutions. This approach allows the company to align with and offer the most expansive list of smart integrations on the market – whether with Google Assistant, Amazon Alexa, or future partnerships.

Specifically, with our open approach, LG is progressing toward incorporating IoT technology throughout the entire journey – including the product design/concept, the launch of new helpful tools, and proactive OTA (Over-The-Air) updates. LG is working with world-class cloud partners from Amazon, Google, and Microsoft, and combining with in-house development to develop, customise, and operate our IoT platforms.

AI is key to differentiating your products on the market by offering more robust opportunities and offerings for the larger consumer base.

What challenges has LG faced moving into AI and how did it overcome them?

The biggest challenge we faced as a whole moving into AI was creating truly meaningful products that will help our customer base with their daily routines and truly improve their lives. Through listening to what they want, we were able to produce a line of help innovations that do just that. 

LG ThinQ products use voice control to interact with users, as well as sensor data and diverse features such as product recognition and learning engine technologies to enhance their performance.

Do you think the smart home is meeting expectations?  

The smart home is a growing trend within the AI industry thanks to the influx of helpful tools introduced across the field. While many advancements have been made in such a short timeframe, we are still in the first inning of this technology adoption.

LG is focused on delivering better consumer benefits with advanced technology that will continue to improve over time. We aim to make the home more proactive and personalised for users based on our behaviour data collected across the products servicing their many needs. Knowing more about our user and their life leads to enhanced performance and, ultimately, to a better life.

Will distributed ledger technologies be important for smart devices and are there any plans at LG ThinQ to use them? 

While we are actively looking at distributed ledgers, including blockchain technology, there is no specific timetable for implementation. We believe this would be useful to enable an open ecosystem where various companies and contributors can participate. 

Is there a specific area of the market you and the LG ThinQ team are excited about?

LG is committed to producing helpful innovations for consumers. One example is our new AI-infused customer service solution, Proactive Customer Care. It’s a new paradigm in customer satisfaction, one that ensures greater value and peace-of-mind for owners of our smart home appliances.  

When it rolls out in the United States next year, Proactive Customer Care will leverage ThinQ AI to provide personalised support, alerting users to issues with their LG appliance, and offering helpful tips and solutions to maximise performance and long product life. Using the latest in AI technology, LG Proactive Customer Care is designed to inform LG smart appliance owners of potential problems before they even occur – it can expedite technician visits, if needed, and offer guidance on how to keep LG’s products functioning optimally.

What did you speak about during this year’s AI Expo North America?

I was thrilled to take part in my first AI & Big Data Expo North America in Santa Clara. As part of my activities onsite, I welcomed interested attendees to visit the panel discussion on “Data and The Customer” where I was joined by fellow industry insiders to discuss in the relationship between the data collected from companies and its customers.  

I also conducted a solo presentation on the topic of “Process Automation from IoT Data.” I helped to define process automation for IoT data and how it is key to use not only the right platform for your business, but also one that allows true process integration and automation for optimisation. This is essential to our work at LG and helps shape our future product launches.

Interested in hearing industry leaders discuss subjects like this? Attend the co-located 5G Expo, IoT Tech Expo, Blockchain Expo, AI & Big Data Expo, and Cyber Security & Cloud Expo World Series with upcoming events in Silicon Valley, London, and Amsterdam.

The post LG ThinQ: Our experience with AI so far and what’s next for the industry appeared first on AI News.

Drive.ai is full of skilled personnel after being founded in 2016 by a pioneering team of graduates from Stanford’s AI lab. With AI talent in short supply, it seems Apple is considering purchasing a whole company to get the skills on its side.

Apple would not get any of Drive.ai’s intellectual property as part of the deal, only the minds behind it. While it’s unclear what Apple is considering paying for the startup, the company was believed to be valued at ~$200 million during a VC round in 2017.

The fact Apple is scoping out talent from a driverless car firm shows Cupertino’s continued interest in the area.

Back in January, Apple pulled around 200 employees off its self-driving car project which made some people question whether Cupertino had the ability (and resolve) to break into such an established industry with a minefield of regulatory needs that vary from location-to-location.

A self-driving car being tested by Apple had a rear-end collision with another vehicle last year. Fortunately, unlike Uber’s self-driving car incident, there were no injuries.

During an interview with CNN last November, Apple CEO Tim Cook expressed that his company is focused on the software side of autonomous vehicles. Acquiring talent from Drive.ai is a surefire way of boosting Apple’s in-house expertise in applying machine learning to cars.

Interested in hearing industry leaders discuss subjects like this and their use cases? Attend the co-located AI & Big Data Expo events with upcoming shows in Silicon Valley, London, and Amsterdam to learn more. Co-located with the IoT Tech Expo, Blockchain Expo, and Cyber Security & Cloud Expo.

The post Apple reportedly wants to ‘acqui-hire’ self-driving car startup Drive.ai appeared first on AI News.