#Platforms powered by artificial intelligence

[esselte974]

The rise of teleworking and teletravel

The travel sector has been a major driver of change in recent years thanks to technology. It’s in these innovations that artificial intelligence, virtual reality and blockchain have been absolutely central to redefining travel. Platforms powered by artificial intelligence now offer personalized travel recommendations and carry out bookings while guaranteeing an exceptional experience. Thanks to…

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Expert Power Platform Services | Navignite LLP

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Simplify Transactions and Boost Efficiency with Our Cash Collection Application

Manual cash collection can lead to inefficiencies and increased risks for businesses. Our cash collection application provides a streamlined solution, tailored to support all business sizes in managing cash effortlessly. Key features include automated invoicing, multi-channel payment options, and comprehensive analytics, all of which simplify the payment process and enhance transparency. The application is designed with a focus on usability and security, ensuring that every transaction is traceable and error-free. With real-time insights and customizable settings, you can adapt the application to align with your business needs. Its robust reporting functions give you a bird’s eye view of financial performance, helping you make data-driven decisions. Move beyond traditional, error-prone cash handling methods and step into the future with a digital approach. With our cash collection application, optimize cash flow and enjoy better financial control at every level of your organization.

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The geniuses at the head of Logitech rigth now...

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Unlocking Opportunities: How a Trusted Education & Career Coach Facilitates Study in the UK

In the vibrant city of Dubai, where innovation meets tradition, the journey of Trusted Education & Career Coaches and consultants unfolds with promising opportunities and transformative innovations. As Dubai continues to position itself as a global hub for education and business, students in the region are witnessing a dynamic evolution in the way they learn, explore career paths, and prepare for the future. In this blog post, we delve into the multifaceted aspects of education and career opportunities for Dubai students, from emerging trends in learning to the diverse pathways in the professional realm.

Virtual Reality Classrooms: Stepping into Tomorrow

Imagine students donning VR headsets, transported to ancient civilizations or exploring molecular structures up close. Virtual reality classrooms are revolutionizing learning, turning textbooks into immersive experiences. In Dubai, where innovation is a way of life, VR classrooms are poised to reshape traditional learning paradigms.

One of the defining characteristics of modern education in Dubai is the integration of cutting-edge technologies that enhance learning experiences. Virtual reality (VR) classrooms have emerged as a game-changer, offering students immersive and interactive environments that transcend traditional teaching methods. Imagine a history lesson where students can virtually visit ancient civilizations or a science class where they explore complex molecular structures up close. VR classrooms not only make learning engaging but also foster deeper understanding and retention of concepts.

[jcmarchi]

Preparing today for tomorrow's AI regulations - AI News

New Post has been published on https://thedigitalinsider.com/preparing-today-for-tomorrows-ai-regulations-ai-news/

Preparing today for tomorrow's AI regulations - AI News

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AI is rapidly becoming ubiquitous across business systems and IT ecosystems, with adoption and development racing faster than anyone could have expected. Today it seems that everywhere we turn, software engineers are building custom models and integrating AI into their products, as business leaders incorporate AI-powered solutions in their working environments.

However, uncertainty about the best way to implement AI is stopping some companies from taking action. Boston Consulting Group’s latest Digital Acceleration Index (DAI), a global survey of 2,700 executives, revealed that only 28% say their organisation is fully prepared for new AI regulation.

Their uncertainty is exacerbated by AI regulations arriving thick and fast: the EU AI act is on the way; Argentina released a draft AI plan; Canada has the AI and Data Act; China has enacted a slew of AI regulations; and the G7 nations launched the “Hiroshima AI process.” Guidelines abound, with the OECD developing AI principles, the UN proposing a new UN AI advisory body, and the Biden administration releasing a blueprint for an AI Bill of Rights (although that could quickly change with the second Trump administration).

Legislation is also coming in individual US states, and is appearing in many industry frameworks. To date, 21 states have enacted laws to regulate AI use in some manner, including the Colourado AI Act, and clauses in California’s CCPA, plus a further 14 states have legislation awaiting approval.

Meanwhile, there are loud voices on both sides of the AI regulation debate. A new survey from SolarWinds shows 88% of IT professionals advocate for stronger regulation, and separate research reveals that 91% of British people want the government to do more to hold businesses accountable for their AI systems. On the other hand, the leaders of over 50 tech companies recently wrote an open letter calling for urgent reform of the EU’s heavy AI regulations, arguing that they stifle innovation.

It’s certainly a tricky period for business leaders and software developers, as regulators scramble to catch up with tech. Of course you want to take advantage of the benefits AI can provide, you can do so in a way that sets you up for compliance with whatever regulatory requirements are coming, and don’t handicap your AI use unnecessarily while your rivals speed ahead.

We don’t have a crystal ball, so we can’t predict the future. But we can share some best practices for setting up systems and procedures that will prepare the ground for AI regulatory compliance.

Map out AI usage in your wider ecosystem

You can’t manage your team’s AI use unless you know about it, but that alone can be a significant challenge. Shadow IT is already the scourge of cybersecurity teams: Employees sign up for SaaS tools without the knowledge of IT departments, leaving an unknown number of solutions and platforms with access to business data and/or systems.

Now security teams also have to grapple with shadow AI. Many apps, chatbots, and other tools incorporate AI, machine learning (ML), or natural language programming (NLP), without such solutions necessarily being obvious AI solutions. When employees log into these solutions without official approval, they bring AI into your systems without your knowledge.

As Opice Blum’s data privacy expert Henrique Fabretti Moraes explained, “Mapping the tools in use – or those intended for use – is crucial for understanding and fine-tuning acceptable use policies and potential mitigation measures to decrease the risks involved in their utilisation.”

Some regulations hold you responsible for AI use by vendors. To take full control of the situation, you need to map all the AI in your, and your partner organisations’ environments. In this regard, using a tool like Harmonic can be instrumental in detecting AI use across the supply chain.

Verify data governance

Data privacy and security are core concerns for all AI regulations, both those already in place and those on the brink of approval.

Your AI use already needs to comply with existing privacy laws like GDPR and CCPR, which require you to know what data your AI can access and what it does with the data, and for you to demonstrate guardrails to protect the data AI uses.

To ensure compliance, you need to put robust data governance rules into place in your organisation, managed by a defined team, and backed up by regular audits. Your policies should include due diligence to evaluate data security and sources of all your tools, including those that use AI, to identify areas of potential bias and privacy risk.

“It is incumbent on organisations to take proactive measures by enhancing data hygiene, enforcing robust AI ethics and assembling the right teams to lead these efforts,” said Rob Johnson, VP and Global Head of Solutions Engineering at SolarWinds. “This proactive stance not only helps with compliance with evolving regulations but also maximises the potential of AI.”

Establish continuous monitoring for your AI systems

Effective monitoring is crucial for managing any area of your business. When it comes to AI, as with other areas of cybersecurity, you need continuous monitoring to ensure that you know what your AI tools are doing, how they are behaving, and what data they are accessing. You also need to audit them regularly to keep on top of AI use in your organisation.

“The idea of using AI to monitor and regulate other AI systems is a crucial development in ensuring these systems are both effective and ethical,” said Cache Merrill, founder of software development company Zibtek. “Currently, techniques like machine learning models that predict other models’ behaviours (meta-models) are employed to monitor AI. The systems analyse patterns and outputs of operational AI to detect anomalies, biases or potential failures before they become critical.”

Cyber GRC automation platform Cypago allows you to run continuous monitoring and regulatory audit evidence collection in the background. The no-code automation allows you to set custom workflow capabilities without technical expertise, so alerts and mitigation actions are triggered instantly according to the controls and thresholds you set up.

Cypago can connect with your various digital platforms, synchronise with virtually any regulatory framework, and turn all relevant controls into automated workflows. Once your integrations and regulatory frameworks are set up, creating custom workflows on the platform is as simple as uploading a spreadsheet.

Use risk assessments as your guidelines

It’s vital to know which of your AI tools are high risk, medium risk, and low risk – for compliance with external regulations, for internal business risk management, and for improving software development workflows. High risk use cases will need more safeguards and evaluation before deployment.

“While AI risk management can be started at any point in the project development,” Ayesha Gulley, an AI policy expert from Holistic AI, said. “Implementing a risk management framework sooner than later can help enterprises increase trust and scale with confidence.”

When you know the risks posed by different AI solutions, you can choose the level of access you’ll grant them to data and critical business systems.

In terms of regulations, the EU AI Act already distinguishes between AI systems with different risk levels, and NIST recommends assessing AI tools based on trustworthiness, social impact, and how humans interact with the system.

Proactively set AI ethics governance

You don’t need to wait for AI regulations to set up ethical AI policies. Allocate responsibility for ethical AI considerations, put together teams, and draw up policies for ethical AI use that include cybersecurity, model validation, transparency, data privacy, and incident reporting.

Plenty of existing frameworks like NIST’s AI RMF and ISO/IEC 42001 recommend AI best practices that you can incorporate into your policies.

“Regulating AI is both necessary and inevitable to ensure ethical and responsible use. While this may introduce complexities, it need not hinder innovation,” said Arik Solomon, CEO and co-founder of Cypago. “By integrating compliance into their internal frameworks and developing policies and processes aligned with regulatory principles, companies in regulated industries can continue to grow and innovate effectively.”

Companies that can demonstrate a proactive approach to ethical AI will be better positioned for compliance. AI regulations aim to ensure transparency and data privacy, so if your goals align with these principles, you’ll be more likely to have policies in place that comply with future regulation. The FairNow platform can help with this process, with tools for managing AI governance, bias checks, and risk assessments in a single location.

Don’t let fear of AI regulation hold you back

AI regulations are still evolving and emerging, creating uncertainty for businesses and developers. But don’t let the fluid situation stop you from benefiting from AI. By proactively implementing policies, workflows, and tools that align with the principles of data privacy, transparency, and ethical use, you can prepare for AI regulations and take advantage of AI-powered possibilities.

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Master Bot Creation with Microsoft Copilot: Expert Tips Revealed

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Unlock Your Creative Genius with Leonardo AI

Today, we're diving into something truly revolutionary in the world of AI and creativity - Leonardo AI!

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Note: This video contains an affiliate link - where if you click on it, there is a possibility that the Manufacturer may provide me a commission.

Whether you're a seasoned professional or just starting out, Leonardo AI is here to revolutionize your creative process. Simply put, Leonardo AI is creativity unleashed. Leverage your generative AI creativity with a unique suite of tools to convey your ideas to the world. Leonardo AI hosts a community of creations while offering generative AI utilities that inspire creative minds in various fields such as character design, game assets, concept art, graphic design, fashion marketing advertising, product photography architecture interior design and so much more!

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3 Less Used but Highly Beneficial Features of Power Apps

Power Apps might be one of the most widely used Low-code Application Development Platform, but it comes a host of features that are not often used, but can have a tremendous impact on making your application more efficient. 

For example,

AI Builder can help you utilize custom AI models to make app design more efficient.

Custom connectors use REST API to expand the functionality by connecting to a wider range of external platforms.

Component libraries can enable you to create and share reusable components across different apps.

 Learn more about how you can use Power Apps to boost operational efficiency, with our best power apps consulting services

[esselte974]

The rise of teleworking and teletravel

The travel sector has been a major driver of change in recent years thanks to technology. It’s in these innovations that artificial intelligence, virtual reality and blockchain have been absolutely central to redefining travel. Platforms powered by artificial intelligence now offer personalized travel recommendations and carry out bookings while guaranteeing an exceptional experience. Thanks to…

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Unlock AI-Powered Topic Recommendations for Targeted Traffic

The Role of Data in AI-Powered Recommendations Harnessing the Power of Data for Personalized Suggestions In the era of digital transformation, data serves as the cornerstone for driving AI-powered recommendations. Through the analysis of user behavior, preferences, and historical data, businesses can derive invaluable insights to offer personalized suggestions. This not only enriches the user…

[atcuality1]

Redefine Customer Engagement with AI-Powered Application Solutions

In today’s digital landscape, customer engagement is more crucial than ever. ATCuality’s AI powered application redefine how businesses interact with their audience, creating personalized experiences that foster loyalty and drive satisfaction. Our applications utilize cutting-edge AI algorithms to analyze customer behavior, preferences, and trends, enabling your business to anticipate needs and respond proactively. Whether you're in e-commerce, finance, or customer service, our AI-powered applications can optimize your customer journey, automate responses, and provide insights that lead to improved service delivery. ATCuality’s commitment to innovation ensures that each AI-powered application is adaptable, scalable, and perfectly aligned with your brand’s voice, keeping your customers engaged and coming back for more.

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Exploring the Benefits of AI SEO Tools for Your Website

AI SEO tools are transforming the way we approach search engine optimization. In today’s fast-paced digital world, leveraging AI SEO tools can give your website a significant edge over the competition. These advanced tools use artificial intelligence to enhance various aspects of SEO, making it easier for your content to rank higher on search engine results pages (SERPs). Let’s dive into how AI…

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The Economic Impact of Ineffective Decision-Making in Global Companies

Ineffective decision-making poses significant risks to global companies, impacting financial performance, operational efficiency, strategic competitiveness, and reputational integrity. However, by leveraging AI insights from Xp, companies can mitigate these risks and make more informed, data-driven decisions. As companies continue to embrace AI as a strategic tool, the role of AI in enhancing decision-making and driving long-term success will only continue to grow, shaping the future of business in profound ways.

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Centralised AI is dangerous: how can we stop it? - AI News

New Post has been published on https://thedigitalinsider.com/centralised-ai-is-dangerous-how-can-we-stop-it-ai-news/

Centralised AI is dangerous: how can we stop it? - AI News

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The intelligence displayed by generative AI chatbots like OpenAI’s ChatGPT has captured the imagination of individuals and corporations, and artificial intelligence has suddenly become the most exciting area of technology innovation.

AI has been recognised as a game changer, with potential to transform many aspects of our lives. From personalised medicine to autonomous vehicles, automated investments to digital assets, the possibilities enabled by AI seem endless.

But as transformational as AI will be, there are a lot of risks posed by this new technology. While fears about a malicious, Skynet-style AI system going rogue are misplaced, the dangers of AI centralisation are not. As companies like Microsoft, Google and Nvidia forge ahead in their pursuit of AI, fears about the concentration of power in the hands of just a few centralised players are becoming more pronounced.

Why should we worry about decentralised AI?

Monopoly power

The most pressing issue arising from centralised AI is the prospect of a few tech giants achieving monopolistic control over the industry. The big tech giants have already accumulated a very significant market share in AI, giving them possession of vast amounts of data. They also control the infrastructure that AI systems run on, enabling them to stifle their competitors, hobble innovation, and perpetuate economic inequality.

By achieving a monopoly over the development of AI, these companies are more likely to have an unfair influence on regulatory frameworks, which they can manipulate to their advantage. It will mean that smaller startups, which lack the enormous resources of big tech giants, will struggle to keep up with the pace of innovation. Those that do survive and look like they might thrive will almost certainly end up being acquired, further concentrating power in the hands of the few. The result will be less diversity in terms of AI development, fewer choices for consumers, and less favourable terms, limiting the use-cases and economic opportunities promised by AI.

Bias and Discrimination

Aside from monopolistic control, there are genuine fears around the bias of AI systems, and these concerns will take on more importance as society increasingly relies on AI.

The risk stems from the fact that organisations are becoming more reliant on automated systems to make decisions in many areas. It’s not unusual for a company to employ AI algorithms to filter job applicants, for example, and the risk is that a biased system could unfairly exclude a subset of candidates based on their ethnicity, age or location. AI is also used by insurance companies to set policy rates, by financial services firms to determine if someone qualifies for a loan and the amount of interest they’ll need to pay, and by law enforcement to determine which areas are more likely to see higher crime. In all of these use-cases, the potential implications of biased AI systems are extremely worrying.

Whether it’s law enforcement targeting minority communities, discriminatory lending practices or something else, centralised AI can potentially exacerbate social inequality and enable systemic discrimination.

Privacy and surveillance

Another risk posed by centralised AI systems is the lack of privacy protections. When just a few big companies control the vast majority of data generated by AI, they gain the ability to carry out unprecedented surveillance on their users. The data accumulated by the most dominant AI platforms can be used to monitor, analyse and predict an individual’s behaviour with incredible accuracy, eroding privacy and increasing the potential for the information to be misused.

It’s of particular concern in countries with authoritarian governments, where data can be weaponised to create more sophisticated tools for monitoring citizens. But even in democratic societies, there is a threat posed by increased surveillance, as exemplified by the revelations of Edward Snowden about the US National Security Agency’s Prism program.

Corporations can also potentially misuse consumer’s data to increase their profits. In addition, when centralised entities accumulate vast amounts of sensitive data, this makes them more lucrative targets for hackers, increasing the risk of data leaks.

Security risks

Issues of national security can also arise due to centralised AI. For instance, there are justified fears that AI systems can be weaponised by nations, used to conduct cyberwarfare, engage in espionage, and develop new weapons systems. AI could become a key tool in future wars, raising the stakes in geopolitical conflicts.

AI systems themselves can also be targeted. As nations increase their reliance on AI, such systems will make for enticing targets, as they are obvious single points of failure. Take out an AI system and you could disrupt the entire traffic flow of cities, take down electrical grids, and more.

Ethics

The other major concern of centralised AI is about ethics. That’s because the handful of companies that control AI systems would gain substantial influence over a society’s cultural norms and values, and might often prioritise profit, creating further ethical concerns.

For example, AI algorithms are already being used widely by social media platforms to moderate content, in an attempt to identify and filter out offensive posts. The worry is that algorithms, either by accident or design, might end up suppressing free speech. 

There is already controversy about the effectiveness of AI-powered moderation systems, with numerous seemingly innocuous posts being blocked or taken down by automated algorithms. This leads to speculation that such systems are not broken but being manipulated behind the scenes based on the political narrative the platform is trying to promote.

The alternative? Decentralised AI

The only logical counterweight to centralised AI is the development of decentralised AI systems that ensure that control of the technology remains in the hands of the majority, rather than the few. By doing this, we can ensure that no single company or entity gains a significant influence over the direction of AI’s development.

When the development and governance of AI is shared by thousands or millions of entities, its progress will be more equitable, with greater alignment to the needs of the individual. The result will be more diverse AI applications, with an almost endless selection of models used by different systems, instead of a few models that dominate the industry.

Decentralised AI systems will also mean checks and balances against the risk of mass surveillance and manipulation of data. Whereas centralised AI can be weaponised and used in a way that’s contrary to the interests of the many, decentralised AI hedges against this kind of oppression.

The main advantage of decentralised AI is that everyone is in control over the technology’s evolution, preventing any single entity from gaining an outsized influence over its development.

How to decentralise AI

Decentralised AI involves a rethink of the layers that make up the AI technology stack, including elements like the infrastructure (compute and networking resources), the data, models, training, inference, and fine-tuning processes.

We can’t just put our hopes in open-source models if the underlying infrastructure remains fully centralised by cloud computing giants like Amazon, Microsoft and Google, for instance. We need to ensure that every aspect of AI is decentralised

The best way to decentralise the AI stack is to break it down into modular components and create markets around them based on supply and demand. One such example of how this can work is Spheron, which has created a Decentralised Physical Infrastructure Network (DePIN) that anyone can participate in.

With Spheron’s DePIN, everyone is free to share their underutilised computing resources, essentially renting them out to those who need infrastructure to host their AI applications. So, a graphic designer who uses a powerful laptop with a GPU can donate processing power to the DePIN when they’re not using it for their own work, and be rewarded with token incentives.

What this means is that the AI infrastructure layer becomes widely distributed and decentralised, with no single provider in control. It’s enabled by blockchain technology and smart contracts, which provide transparency, immutability and automation.

DePIN can also work for open-source models and underlying data. For instance, it’s possible to share training datasets on a decentralised network like Qubic, which will make sure the provider of that data is rewarded each time their information is accessed by an AI system.

To ensure access and permissions are decentralised, every part of the technology stack is distributed in this way. However, the AI industry currently struggles to provide such a level of decentralisation. Although open-source models have become extremely popular among AI developers, most people continue to rely on proprietary cloud networks, meaning the training and inference processes are heavily centralised.

But there are strong incentives for decentralisation to win out. One of the primary advantages of DePIN networks, for example, is that they help to reduce overheads. Because networks like Spheron don’t rely on intermediaires, participants don’t need to make any payments or share revenue with third-parties. Moreover, they can afford to be more competitive in terms of pricing than corporations that are under pressure to grow profitability.

Decentralisation must win

The future of AI holds a lot of potential, but it’s also perilous. While the capabilities of AI systems have improved dramatically in the last few years, most of the advances have been made by all-powerful companies and that has resulted in an increase in their influence over the industry. There’s a price to pay for this, not just in monetary terms.

The only reasonable alternative is to promote the greater adoption of decentralised AI, which can enhance accessibility and ensure a greater flexibility of AI. By allowing everyone to participate in the development of AI on an equal footing, we’ll see more diverse, interesting, and useful applications that can benefit everyone equally, as well as putting their users first.

Building a decentralised AI future will involve a great deal of coordination and collaboration across every layer of the AI stack. Fortunately, there are strong incentives for participants to do just that. And again, the incentives are not just monetary.

[digitalmarketing6669]

Canvas App Development with Copilot in Power Apps