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[waldron] 17/2/2023 06:45

Privacy Regulators Step Up Oversight of AI Use in Europe

European privacy regulators are intensifying their scrutiny of companies' use of artificial intelligence, hiring experts and opening new units to crack down on data violations.

Companies' increased uptake of AI for a variety of applications, ranging from automated human-resources processes to retail chatbots and fraud-prevention technologies, are driving regulators to beef up their abilities to investigate potential violations of the European Union's General Data Protection Regulation.

[hedgehog 100] 04/2/2023 15:15

"Ghulam Mustafa Shoaib
Jan 21 · 3 min read

Human Resource Management Challenges and The Role of Artificial Intelligence in 2023

Human resource management (HRM) is a critical aspect of any organization as it involves managing the workforce and ensuring that their needs are met. However, HRM faces several challenges that can hinder the performance of the organization. In this article, we will discuss some of the challenges faced by HRM and the role of artificial intelligence (AI) in addressing these challenges in 2023.

Challenges Faced by Human Resource Management

1. Attracting and Retaining Talent

One of the biggest challenges faced by HRM is attracting and retaining top talent. Organizations struggle to find and retain the best employees in a highly competitive job market. This is especially true for high-demand roles such as data scientists, software engineers, and digital marketing specialists.

2. Managing Employee Diversity and Inclusion

Another significant challenge faced by HRM is managing employee diversity and inclusion. With the increasing diversity of the workforce, organizations must ensure that all employees are treated fairly and with respect. This includes creating a culture of inclusion, providing training and education, and addressing discrimination and bias.

3. Managing Employee Engagement

HRM also faces the challenge of managing employee engagement. With the rise of remote work and flexible schedules, keeping employees engaged and motivated can be difficult. This can lead to decreased productivity and higher turnover rates.

4. Managing Employee Data

HRM also faces the challenge of managing employee data. With the increasing use of technology, organizations must ensure that employee data is accurate, up-to-date, and secure. This includes managing employee information, performance data, and compliance with data privacy laws.

The Role of Artificial Intelligence in Addressing HRM Challenges

1. Attracting and Retaining Talent

AI can help HRM attract and retain talent by automating the recruitment process. This includes using AI-powered chatbots to answer candidate questions, using machine learning algorithms to analyze resumes and identify the best candidates, and using predictive analytics to identify high-potential employees.

2. Managing Employee Diversity and Inclusion

AI can also help HRM manage employee diversity and inclusion by automating the performance review process. This includes using machine learning algorithms to identify bias and discrimination in performance evaluations, providing training and education to employees on diversity and inclusion, and addressing discrimination and bias.

3. Managing Employee Engagement

AI can help HRM manage employee engagement by automating the employee engagement survey process. This includes using machine learning algorithms to identify areas of improvement, providing feedback and coaching to employees, and tracking progress over time.

4. Managing Employee Data

AI can help HRM manage employee data by automating the data management process. This includes using machine learning algorithms to identify errors and inconsistencies, providing real-time updates, and ensuring compliance with data privacy laws.

Conclusion

HRM faces several challenges that can hinder the performance of the organization. However, AI can help address these challenges by automating recruitment, performance evaluations, engagement surveys, and data management. As we move into 2023, we can expect to see more organizations leveraging AI to improve their HRM processes."

[hedgehog 100] 29/1/2023 12:18

Also from the website of Grosvenor Technology, NWT's Human Capital Management (HCM) and access control subsidiary, another excellent article by GT's MD:-

"Insights | Human Capital Management

HCM Growth Expected To Hit An All-Time High

With such widespread adoption of HCM solutions, the market will likely enjoy significant growth over the next few years

Colin Leatherbarrow
Managing Director

HCM market value is tipped to soar, with growth being guided by technological leaps and a move towards a distributed workforce.

Increasingly, organisations are seeing the advantage of centring human capital management technology (HCM) within their HR, payroll, and recruitment functions.

With such widespread adoption of HCM solutions, the market will likely enjoy significant growth over the next few years. There are variances when assessing just how much the sector will increase in value. However, according to the vast majority of recent HCM forecasts, billions of dollars are expected to be added to its value over the next decade, with the US and North America leading the charge.

Technavio’s May 2022 report predicts that the global HCM market will increase by $12.16 billion between 2020 and 2025.

The HCM market observed year-on-year growth of 9.52% in 2021, and it’s thought that we’ll see that growth momentum accelerating at a CAGR of 10.57% during the forecast period. North America is anticipated to have the largest market share, with around 34% of the overall market growth.

The longer-term forecast is also optimistic. A report by Fortune Business Insights predicted the following: “The global HCM market size was $23.6 billion in 2021. The market is expected to grow to $25.53 billion by 2029, exhibiting a CAGR of 9.1% during the forecast period.

“The global impact of COVID-19 has been unprecedented and staggering, with HCM experiencing high-than-anticipated demand across all regions compared to pre-pandemic levels.”

North America has accounted for nearly half the market for the past two years, with an estimated value of over $10 billion – a trend that’s likely to continue. The report noted: “North America is anticipated to hold a dominant position in the global market. The rising adoption of advanced technologies, smartphones, and workforce analytics solutions is expected to spur the region’s market growth.”

So, the rapid and sustained growth value of Human Capital Management over the next ten years looks assured, but what is the motivation behind this surge in ongoing demand?

Technology

HCM capabilities have come a long way, propelled by advances in enterprise technology. In the world of HCM, businesses are increasingly using software with artificial intelligence (AI) and robotic process automation (RPA) capabilities.

In the US, the battle for talent is fierce; hiring managers are using AI and machine learning tools built into HCM software to filter hundreds of candidates and select those most suited to the position, reducing admin time significantly.

Businesses are widely utilising RPA as part of their HCM strategy. RPA is effectively a digital worker that automates repetitive and time-consuming tasks, such as payroll, data input, and remittance, enabling HR teams to focus on high-level tasks.

The Cloud

Enterprises worldwide are turning to cloud-based solutions to hone efficiency, improve output, and reduce costs. In the HCM sector, customers can choose from many bespoke cloud-based HCM solutions that can be customised to suit the needs of their organisation.

These cloud solutions connect all HR processes across a business, meaning companies with multiple locations across the US and further afield can collaborate on recruitment, talent acquisition, employee relations, and other HR functions such as payroll and remittance.

This is a vast improvement on previous methods, where a business would have stored sensitive HCM information locally on one or two machines.

The Pandemic

No single corner of the business world hasn’t seen change brought about by the pandemic, and HCM is no exception. It changed the way businesses and their people work, with hybrid and remote working becoming the norm for many.

As a result, cloud-based solutions and collaboration tools such as HCM have been brought in since they allow HR and personnel teams to handle onboarding, employee communications, and payroll functions efficiently.

HCM solutions have aided the continuation of businesses’ operations and allowed them to stay connected to their employees during a time of real upheaval.

Having experienced the benefits of HCM, the business world welcomes these solutions in increasing numbers. By the end of this year, Gartner predicts organisations will retain the majority of solutions deployed to support new ways of working.

If you’d like to join the ranks of the many businesses that have embraced HCM solutions to streamline and manage their HR processes, contact one of our team today."

[waldron] 25/6/2022 08:06

venturebeat.com/2022/06/24/for-shell-ai-and-data-is-as-critical-as-oil/

[grupo guitarlumber] 02/6/2022 09:33

WIND TECHNOLOGY.COM

June 2, 2022
Engie, Google Cloud to develop AI solution for wind energy

The AI solution will predict price and quantity of wind power to be sold in the market.
The project is expected to benefit the wind facilities across the globe. Credit: Pexels from Pixabay.

French utility company Engie has partnered with tech giant Google for developing an artificial intelligence (AI)-based wind energy solution.

Under this new partnership, Engie and Google Cloud’s AI Services and Industry Solutions (AIIS) will work together to develop a solution that can predict the price and quantity of wind power to be sold in the market.

Google Cloud Global Energy Solutions director Larry COCHRANE said: “At Google Cloud, we believe that more accurate data and predictions of wind power production will be valuable to electricity grids, creating benefits for consumers and making wind more competitive with fossil fuels.

“We are delighted to work with ENGIE on this project, which can accelerate Europe’s clean energy transition, while laying the groundwork for wind farms around the world to benefit from improved forecasting via Artificial Intelligence.”

AI solution will make use of performant and scalable data system as well as advanced machine learning (ML) algorithms to support decision making process.

Once completed, the project is expected to benefit the wind facilities across the globe with increased forecasting capabilities using AI.

ENGIE Global Energy Management & Sales executive committee member Alexandre Cosquer said: “ENGIE’s business entity ‘Global Energy Management & Sales’ has been developing its systems in the last decade to cope with the challenges involved in managing renewables assets.

“With already a double expertise in risk and data management, we were looking to intensify the renewables development, and to partner up with one of the most superior experts not only in data management but also in Machine Learning technology.

“Data, Digitalization and Risk Management are key enablers to bring value and accelerate the decarbonation of our power grids; in that context, a partnership with Google was obvious.”

[sarkasm] 28/2/2022 11:10

Feature
Shell sees AI as fuel for its sustainability goals

The energy giant’s dual-cloud transformation includes a data lake architecture that AI chief Dan Jeavons says is catalyzing business efficiencies and will prove key in cutting carbon emissions over time.

By Paula Rooney

Senior Writer, CIO

Feb 28, 2022 2:00 am PST


Energy giants are under significant pressure by governments and consumers to reduce carbon emissions. For multinational oil and gas company Shell, artificial intelligence may be a key catalyst for fulfilling that long-term goal.

The London-headquartered energy company’s ongoing digital transformation, fueled by a hybrid cloud platform and Databricks data lake house, includes a mix of AI technologies aimed at optimizing business efficiencies and profits and, over time, reducing its carbon footprint.

“AI has become a very core part of our overall digital transformation journey,” says Shell’s chief AI guru Dan Jeavons, noting that Shell works with several AI companies, including Microsoft and C3.ai, but has been in a close partnership with Databricks since 2015. Roughly 20 Databricks employees are assigned to the Shell account.

Jeavons, who has served as vice president of computational science and digital innovation at Shell for just six months, is the former general manager of data science at Shell and has been knee deep in data science since 2015.

In his new role, reporting to Shell Group CIO Jay Crotts, Jeavons is tasked with employing AI as well as emerging technologies such as blockchain, IoT, and edge computing to overhaul Shell’s future technology strategy and help steer its commitment to reduce its carbon footprint to become a net-zero emissions energy business by 2050.

Gartner AI analyst Anthony Mullens says Shell’s AI implementations are beyond what most other companies are doing. “Shell is over the hump in terms of initial experimentation right across the organization,” says Mullens, pointing to Shell’s Center for Excellence and participation in OpenAI.



Jeavons’ group has several hundred data scientists using AI — mostly on Databricks’ Spark-based platform — writing algorithms to execute tasks such as improving the cycle times of subsurface processing, optimizing the performance of assets, predicting when and if various pieces of equipment might fail, as well as improving offerings to customers.

“Given the threat of climate change, we need to move to a lower carbon energy system and digital plays a key role in that,” Jeavons says, noting many of the CO2 monitoring data streams will flow through Databricks AI platform. “Digital technology is one of the core levers that we can pull in order to significantly reduce the CO2 footprint of the energy system.”

According to Jeavons, Shell’s use of digital technology reduced the CO2 emissions of one liquefied natural gas (LNG) facility by as much as 130 kilotons per year — equivalent to removing 28,000 US vehicles off the road for a year.

“Many of the people that work for us have a sense of compelling purpose actually applying AI to try to accelerate energy transition,” he says. “But I’m not going to pretend it’s easy.”


Data is the foundation

As part of its digital transformation, Shell relies on two public clouds, Microsoft Azure and AWS, as well as Docker and Kubernetes containerization technologies, to run increasingly advanced workloads for various aspects of its $210 billion oil and gas business.

Shell

A key facet of that strategy, Jeavons says, is the company’s foundational data layer — a pool from which multiple tools and technologies can access data systematically.

“Having a dual-cloud strategy means you need some consistency as to how you want to manage and integrate your data. Now of course, not all data is going to be in one place. You have a variety of databases; everybody does,” Jeavons says. “But from an analytics perspective, more and more, we’re consolidating certain types of data into an integrated lake house architecture based on Databricks.”

On the analytics side, integrating data into a common layer in Databricks’ Delta Lake and using Python in a common platform allows simple queries and classical reporting query integration with visualization tools such as Power BI.

But on the AI front, it “also allows you to run the machine learning workloads all on the same platform,” Jeavons says. “For me, that’s been a step change.”

For example, Shell has integrated all its global time-series data — information such as temperature, pressure, a particular piece of equipment — into a common cloud based on Delta Lake, enabling the energy giant to keep its finger on the pulse of most global assets, including data from refineries, plants, upstream facilities, winds farms, and solar panels. “It’s 1.9 trillion rows of data aggregated today, which is a huge amount globally,” Jeavons says. “We measure everywhere.”


Shell’s AI efforts also include performing failure predictions and assessing the integrity of its energy assets by using machine vision to identify corrosion. “We’re also using AI to develop technology which can optimize the assets and make them run more efficiently at scale and optimize based on historical performance,” Jeavons says, noting that, while much of Shell’s AI magic is due the implementation of its data lake, none of it could be achieved without cloud advancements.

“Really, the key thing has been the maturing of the clouds and the ability to remove some additional layers that we had [in order] to take data directly from the plants and stream it into the cloud. That’s been helpful in driving both data analytics but also the AI strategy,” he says.


The road ahead

In total, Shell has about 350 professional data scientists and roughly 4,000 professional software engineers working remotely and/or in one of Shell’s hubs in Bangalore, India; the UK; the Netherlands, and Houston, Texas.

Aside from the cloud and data lake house, Shell has also moved to advanced development tools such as Microsoft Azure DevOps and is integrating GitHub into its developers’ ways of working. It is also deploying more mature code screening tools for the cloud, running “proper” CI/CD workflows and monitoring “north” of 10,000 pieces of equipment globally using AI as part of its remote surveillance centers, Jeavons says.

But it is the development of a common lake house architecture that has made the most difference, giving Shell “an integrated data layer that provides visibility of all the data across our business” in a consistent way, Jeavons say.

“We were a very early adopter of Delta,” he says. “For a while, it was more in proof-of-concept mode than in deployed at scale load. It’s really been in the past 18 months where we’ve seen a step change and we’ve been running quite hard.”

Change management, however, remains one of the company’s biggest challenges.

“How do you embed the technology into the business process and make it usable and a part of what happens every day and developing algorithms that work? I’m not going to underplay how difficult it is. It’s non-trivial,” Jeavons says. “It’s tougher to develop the adoption [of AI] at scale. It’s still very much a journey and we’ve made some strides but there’s a lot more to do.”

[ariane] 23/2/2022 11:52

Looking forward to an early warm Spring

[grupo guitarlumber] 22/2/2022 16:45

CITYA.M


Tuesday 22 February 2022 4:19 pm

Robots and AI’s not allowed to copyright artworks, US Copyright Office says

By: Louis Goss

The US Copyright Office (USCO) has said Artificial Intelligences (AI’s) should not be allowed to patent their own work, after ruling that copyright claims can only be registered on work containing element of human authorship.

The Copyright Office ruled that artificial intelligences (AI’s) should not be allowed to secure copyright on any content they produce, after computer scientist Stephen Thaler set out to register a copyright claim for a computer-generated artwork produced by his “Creativity Machine”.

A three-person board at the USCO ruled that in order to secure a copyright registration, any claim must have an element of “human authorship,” as it ruled that copyright law only protects “the fruits of intellectual labour” that are “founded in the creative powers of the human mind.”

The ruling comes after Thaler first sought to register a copyright claim on a 2D image created by his Creativity Machine, called “A Recent Entrance to Paradise.”

In 2019, a copyright specialist refused to register the claim, on the grounds that the artwork “lacks the human authorship necessary to support a copyright claim.”

Thaler later filed a second request as he argued the USCO should allow computers to copyright “machine-generated works” as he claimed that doing so would “further the underlying goals of copyright law.”

He argued that the Copyright Office is relying on case law from the “Gilded Age” to determine whether AI and machine-made artworks can be patented, as he said that computer generated images fall under the USCO’s work-for-hire clause.

The Copyright Office board ruled that as the artwork was autonomously created by an AI, it is not protected under copyright law, as the laws only apply to works by humans. As such, the USCO refused to grant Thaler a patent.

[grupo guitarlumber] 08/2/2022 18:00

EU plans multi-billion euro boost for chip production to ease supply disruptions


Published Tue, Feb 8 202211:37 AM EST

Updated An Hour Ago

Silvia Amaro
@Silvia_Amaro
CNBC

Key Points

Boosting chip production in the European Union was one of the key promises that von der Leyen made in September when addressing European lawmakers.

The proposals come at a time when the EU is looking to step up its role in the world of tech.

[waldron] 12/1/2022 10:33

BT engineers new digital network infrastructure for ABB

12 January 2022 - 10:00AM

PR Newswire (US)


LONDON, Jan. 12, 2022 /PRNewswire/ -- BT today announced it is working with ABB to elevate its internationally managed communications infrastructure to new levels of performance, choice and agility to support the company's new operating model. It follows the signing of a new contract between the two companies.

BT transforms ABB's network infrastructure to create a sustainable, resilient and secure core platform featuring a highly automated and data-driven managed service.

The new contract builds on an existing agreement, signed in 2014, under which BT consolidated and optimised the leading global technology company's international communications infrastructure. Working with ABB's Information Systems team, BT will now transform the network infrastructure to create a sustainable, resilient and secure core platform featuring a highly automated and data-driven managed service.

Security is a top priority for ABB as it executes its cloud strategy, which includes consolidating data centres and moving more applications and data into the cloud. BT will enable ABB's cloud-first ambitions with an end-to-end, compliant, multi-layered cyber security environment. It will deploy, manage and monitor over 1,100 end-point devices, continuously verifying every device, user and application accessing the network.

The communications infrastructure will reliably and securely connect people, devices and machines at over 600 facilities in 60 countries. Using the latest software-defined networking technology, it will offer ABB a choice of connectivity options for each site, including 5G access.

It will also provide ABB with a new software-driven platform delivered over Wifi 6 to enable mobility and digital manufacturing concepts, such as robotics, Internet of Things (IoT) and Big Data technologies at production sites. Both companies have committed to a co-innovation fund as part of the contract.

By choosing BT, ABB is ensuring its network is delivered by a provider using 100 per cent renewable electricity globally with a commitment to achieving net zero emissions across all its operations by 2030.

"ABB's world-class technology and digital capabilities are deeply embedded in our DNA. Maintaining and improving our innovation, technology and digital leadership is a strategic priority across the company," said Alec Joannou, Group CIO, ABB. "BT is a great fit for our Information Systems function. As our trusted partner, it has helped us keep pace with a dynamic digital landscape and is now evolving our communications infrastructure to support our digital ambitions."

"The cloud-first network and digital managed services we're delivering will further enhance agility across ABB's businesses," said Bas Burger, CEO, Global, BT. "The unique trust between our two companies empowers us to push ahead as we connect ABB's people, devices and machines in a sustainable and responsible way."

About BT

BT Group is the UK's leading telecommunications and network provider and a leading provider of global communications services and solutions, serving customers in 180 countries. Its principal activities in the UK include the provision of fixed voice, mobile, broadband and TV (including Sport) and a range of products and services over converged fixed and mobile networks to consumer, business and public sector customers. For its global customers, BT provides managed services, security and network and IT infrastructure services to support their operations all over the world. BT consists of four customer-facing units: Consumer, Enterprise, Global and its wholly-owned subsidiary, Openreach, which provides access network services to over 650 communications provider customers who sell phone, broadband and Ethernet services to homes and businesses across the UK.

For the year ended 31 March 2021, BT Group's reported revenue was £21,331m with reported profit before taxation of £1,804m.

British Telecommunications plc is a wholly-owned subsidiary of BT Group plc and encompasses virtually all businesses and assets of the BT Group. BT Group plc is listed on the London Stock Exchange.

For more information, visit www.bt.com/about

Contact: [e-mail]

Cision View original content to download multimedia:

SOURCE BT

[gibbs1] 11/10/2021 09:41

Seeing Machines Ltd. said Monday it has signed a framework deal with Shell Global Solutions International BV to provide its Guardian driver distraction and fatigue technology.

The designer of artificial-intelligence-powered monitoring systems said Shell plans to start the deployment of Guardian in 2021, though it could take several years to be fully implemented.

Shares at 0750 GMT were up 5.0% at 9.61 pence.



Write to Jaime Llinares Taboada at [e-mail]; @JaimeLlinaresT



(END) Dow Jones Newswires

October 11, 2021 04:17 ET (08:17 GMT)

[waldron] 06/10/2021 19:31

AI-enabled operations of telcos for digitalisation of industries

THE ARTICLES ON THESE PAGES ARE PRODUCED BY BUSINESS REPORTER, WHICH TAKES SOLE RESPONSIBILITY FOR THE CONTENTS

Provided by
Mounir Ladki
President and CTO, MYCOM OSI

48 minutes ago


How software and AI are becoming the brain of telecom networks to reinforce digital businesses.

5G is the common denominator behind digitalisation and automation, the connected world, and smart enterprises. While industries are transforming and automating at an unheralded pace, 5G service providers are being plunged into the role of agents for the success of those industries, and not without benefits – there are massive monetisation opportunities for service providers.

A digital economy worth almost a trillion dollars hinges on the capability of the underpinning networks to deliver. But to unlock the network’s full potential, telcos might want to take a leaf from the hyperscalers and their use of automation and intelligence technologies. And while billions are being spent on the development of IoT, Industry 4.0 and the connected world, far less is devoted to the automation and intelligent technologies that could enhance the quality and reliability of the telecom networks that will form the backbone of the new trillion-dollar economy.

The future role of telcos

Telecom networks need to offer advanced connectivity services that are on-demand and delivered in real-time with unprecedented availability and quality of service. The expected experience of the enterprise user is a swift response, and the expected behaviour of the enterprise user – similar to a hyperscaler company’s user – is the choice to churn between networks when services don’t perform. Enterprise users would expect that guaranteed SLAs for use-cases, such as connected vehicles, industrial processes and remote healthcare are always met. SLA guarantees are mostly integral to the enterprise’s business model, and to make the model work, telcos will need to work doubly hard.

While 5G networks promise a high level of response and service using network slicing, edge connectivity and private networks , they still lag in offering automation and intelligence, important for high agility and assure the promises are maintained over time. By introducing these, telco network efficiency would increase by an order of magnitude, reinforcing service provider business.
Are 5G networks equipped to assure the enterprise demand?

As billions of new devices are added and use cases from multiple industries boom, 5G networks are under huge pressure to manage the complexity, scale and speed of Industry 4.0 and smart enterprise services. 5G networks need to be fully autonomic to deal with this challenge. The term autonomic relates to an automated, intelligent, predictive, and experience-driven way of operating the network. This is missing today.

A higher level of intelligence is required to deal with the immense complexity, scale and diversity of devices and use-cases powered by the network, that goes beyond the precision required to run the network efficiently and effectively. The 5G network of today has become highly disaggregated (Open RAN, VRAN, CRAN, Edge, etc.) and the intelligence is now delegated to the edge and private access networks. Assuring services now requires a system that uses AI to deal with the diverse and distributed nature of 5G; to act as the nerve centre of the network and command its mission-critical and business-reinforcing operations. This will lead the modern 5G (and future connectivity technologies) to the reality of an autonomic telco network.
BRAIN (Business Reinforcement using Artificial Intelligence for Networks)*

The autonomic network will be realised only if AI is used to assure its agile operations and to produce intelligent analytics to ensure that business problems are immediately and accurately resolved.

Since service providers are quickly embracing a collaborative approach to co-innovating and co-creating services using AI for operations and analytics, this is the perfect time for them to collaborate with assurance vendors to enrich the service provider’s telco data lakes, which will guarantee a high degree of accuracy on the AI/ML models. This democratisation of access to network data through a BRAIN system will allow service providers to innovate faster.

BRAIN is not only about the use of AI to assure future networks intelligently and for their autonomic operations. It is a powerful concept to reinforce and realise business objectives, as billions of dollars are being spent on making Industry 4.0 a success. The components of BRAIN are intelligent software (service assurance), big data, AI, cloud and open API. The BRAIN is an enabler of several capabilities (including real-time orchestration, automation, and analytics) that enables service providers to ensure high performance and reliability for Industry 4.0 and private mobile networks.
The way forward

Having served tier-one telcos around the world for the past two decades, MYCOM OSI has embarked on an exciting new journey of building the BRAIN for public and private mobile networks through collaborative work across the industry. MYCOM OSI plays a key role in bringing the concept to the real world. Working with an ecosystem of hyperscalers, technology companies and system integrators, the BRAIN will enable the democratisation of the network data that is critical for the success of tomorrow’s autonomic telcos, private mobile networks, and smart enterprise networks.

*BRAIN (Business Reinforcement using Artificial Intelligence for Networks) is a MYCOM OSI concept.

To find out more, please visit www.mycom-osi.com

Originally published on Business Reporter

[hedgehog 100] 01/9/2021 20:26

It's interesting to see robotics-AI stock PRSM up 32.2% yesterday, on takeover speculation -

31/08/2021 15:56 ALNC TOP NEWS: Blue Prism in talks for private equity buyout, shares surge
31/08/2021 14:56 UKREG Blue Prism Group PLC Response to speculation



This highlights the robotics-AI aspects of other stocks, such as Osirium Technologies (OSI).
Currently just 24p, market cap. £7.05M.

"27 MARCH 2018
IT security, efficiency, and the robots making it happen
Osirium
Robotic Process Automation (RPA) and Artificial Intelligence (AI) are driving technological advancements never seen before, pushing business into a new era. Just as industrialisation transformed the relationship between construction workers and heavy machinery, software robots and human workers are set to form a partnership which combines efficiency and security as personnel are replaced by RPA and reassigned to more important and higher cognitive tasks.
In the IT security world, with the last 12 months showing us some of terrifying data breaches we’ve ever seen, robots might just be the key to our salvation…
Robots and IT service delivery ..."


"21 SEPTEMBER 2018
Osirium and RazorSecure Strategic Alliance
Andy Harris
... Machine Learning and Artificial Intelligence
... New paradigms in Task Automation and RPA (Robotic Process Automation) ... "

[maywillow] 29/6/2021 10:24

Ai-Da the robot artist

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