The role of GenAI in reshaping how we interpret and leverage information cannot be overstated, and it is truly proving to be a differentiator, further separating early adopters and laggards. Traditionally, data has been siloed within specialist teams—scientists, engineers, and analysts—leading to bottlenecks that stifle agility and slow decision-making. By implementing GenAI products, businesses can break down these silos by enabling users at all levels to engage directly with data, putting data insights in the hands of every business user, engineer and application builder. When leveraging GenAI for data analytics, businesses are able to guide and automate certain tasks, cutting down the time this would normally take between different data teams, which in turn empowers users to be more productive and help employees serve themselves more efficiently.

Early adopters of GenAI for data analytics, like EcoLab and Verizon, are reaping significant rewards. EcoLab, a global sustainability provider, has trained GenAI on clients’ operational and financial data to quickly and effectively identify the best resources for them, reducing the cost of time and resources. This proves that companies who have already adopted the technology across their operations are seeing benefits such as democratised data access, the ability to deliver actionable insights rapidly and monitor the benefits which have the ability to transform the company. Through being able to leverage, analyse and make data-driven decisions quicker and more effectively through GenAI, employees can prioritise other operations, which accelerates a company’s growth and enables them to scale quicker.

As well as reporting operational benefits, companies are seeing a measurable return on investment with GenAI, reaffirming the technology as both a financial asset and a key competitive differentiator. For example, Verizon—the telecoms giant—has developed a “centre of excellence” which allows them to monitor the ROI they are receiving for GenAI, meaning they can constantly monitor the financial benefits they’re receiving from the technology, and where it’s proving to be most beneficial. When investments are made, it is important to show the value and return making it suitable for the bottom line.

Democratised data access for decision making across levels of a business enables businesses to grow, scale and become more efficient.  This was highlighted in a recent report by MIT sponsored by ThoughtSpot found that nearly half of adopters of GenAI for analytics anticipate a 100% or greater ROI within three years. By moving away from a centralised framework, businesses enhance accessibility to data, and improve performance of data-driven decisions, which is beneficial for businesses in the long-run.

It’s a fact that innovation and originality is also crucial to empower and drive businesses towards efficiency and growth. GenAI for data analytics plays an important role in business innovation as through extracting insights from multiple datasets, GenAI can build a complete and personalise of different customers’ behaviour and habits in an instant. When using traditional in-house teams, although they may be able to reach the same conclusion, they may struggle to do it as quickly. Whereas harnessing GenAI for data analytics means results are achieved quicker, and therefore more can be achieved each day.

In the same way that GenAI has been widely adopted across businesses, agentic AI is now rapidly making inroads into businesses, and already transforming everyday operations. Agentic AI is offering businesses a step beyond GenAI—through operating autonomously to perform tasks in a human-like way. Agentic AI uses large language models (LLMs) to manage multiple agents, which can handle a vast range of operations from data search and analysis to driving complex data-led decisions. The technology’s systems go beyond when it comes to automating end-to-end processes, reducing manual effort and increasing efficiency across operations, to the point where they are widely described as being human-like.

Just as companies have been integrating GenAI products, more companies are now beginning to integrate agentic AI products into their ecosystems. Autonomous agents, such as Spotter, are allowing businesses to work with data in ways that hadn’t been previously possible – allowing them to converse with the system in the same way they would a human data analyst. By embedding the products into their existing business applications, when users ask questions of their data, they can now get the structured and efficient answers they need, which are adapted to both the industry and persona of its users.

To unlock transformative business value, companies must integrate GenAI and agentic AI without delay. Staying ahead of the curve ensures they dismantle bottlenecks, achieve rapid, data-driven insights, and enjoy substantial ROI—essential advantages in an AI-powered future.

The post From assistance to agency: how GenAI for analytics is unlocking measurable business value appeared first on TechInformed.

The UK government has been criticised by campaigners for creative industries after it proposed letting AI companies train their models on copyrighted works.

The proposal, which suggests that AI firms should freely leverage a new copyright exemption while training their algorithms, is “entirely untested and unevidenced” said crossbench peer Beeban Kidron, who campaigns to protect artist and creative rights.

Singer and songwriter Sir Paul McCartney warned AI could “just take over” if the firms writing LLMs are allowed to ignore copyright, but the government warned “legal uncertainty is undermining investment in and adoption of AI technology.”

Read more

Munich Airport aims to boost data use and cut wait times with AIRHART deployment

Munich Airport has unveiled plans for the next stage of its digital transformation after agreeing on a deal to implement the AIRHART data platform.

AIRHART, which is already in operation at Copenhagen Airport, uses real-time data analytics to improve the flow of passengers as they travel through an airport. It uses AI to optimise landing gates, predict bottlenecks and tie together all the different datasets and systems used in an airport.

AIRHART was created by Danish tech firm Netcompany in partnership with Copenhagen Airport and was deployed last year.

Munich Airport is Europe’s tenth busiest airport with over 50 million passengers a year.

“Munich Airport has a strong commitment to innovation and creating a seamless experience for the millions of passengers who visit and transfer at our hub. The implementation of AIRHART and our partnership with Netcompany is a significant step towards that objective,” says Florian Lesch, Senior Vice President IT at Munich Airport.

Read all about how it transformed the Danish airport’s operations

BlackBerry sells endpoint security arm Cylance to Arctic Wolf in huge loss

BlackBerry has reached a $160 million deal to sell Cylance to Arctic Wolf six years after it bought the endpoint detection and response vendor for $1.4 billion.

Arctic Wolf said the acquisition of the AI-powered cyber firm will bolster its EDR offerings, subject to closure of the deal which is expected to come in BlackBerry’s fourth fiscal quarter.

BlackBerry’s acquisition of Cylance in 2018 marked a significant step for the Canadian firm as it pivoted away from being a device manufacturer to focus on enterprise solutions, including security. It was BlackBerry’s largest ever acquisition at the time.

Arctic Wolf will pay $80 million once the deal closes, $40 million around a year later, and chip in 5.5 million shares too.

“Security has an operations and effectiveness problem and endpoint solutions alone have failed to live up to the outcomes they have promised for years,” said Nick Schneider, president and chief executive officer, Arctic Wolf.

“By incorporating Cylance’s endpoint security capabilities into our open-XDR Aurora platform, we will be addressing a rampant need for a truly unified, effective security operations that delivers better outcomes for customers. We believe we will be able to rapidly eliminate alert fatigue, reduce total risk exposure, and help customers unlock further value with our warranty and insurability programs.”

Read more

ChatGPT search made available for all users

OpenAI is making ChatGPT’s search engine function available for all users, including an optimised version for mobile.

The generative AI platform first launched a search function back in October, but it was initially only available for paid subscribers. However, OpenAI revealed as part of its “12 days of ship-mas” the function will unlock for free tiers of ChatGPT from today.

On mobile, the search function will appear more like a traditional search engine, including answers more relevant based on location data.

Another feature aims to make ChatGPT search faster when you’re looking for certain sites, such as “hotel booking websites.” Now, ChatGPT will surface links to websites before taking the time to provide more information about each option.

Additionally, the AI can also automatically provide up-to-date information from the web when using Advanced Voice Mode, though that remains only available to paid users.

Read more

The post UK mulls copyright exemption for AI and BlackBerry incurs loss on Cylance sale appeared first on TechInformed.

At a glance…

• Accenture and Nvidia partnered to advance agentic AI
• The US presidential election shook up the tech sector
• Vodafone and Three merger created UK telco buzz

October: Big Movements in Big Tech

Google invested $1 billion into data centre regions in Thailand

Data centre and cloud investments continued to surge in the last quarter of the year, as Alphabet’s Google announced a $1 billion investment towards building data centre regions in Thailand.

The goal was to support AI adoption in Southeast Asia — as Deloitte forecasted, the investment would create an average of 14,000 jobs annually by 2029.

Accenture and Nvidia expanded their partnership to scale agentic AI adoption

In terms of Gen AI, there’s a new kid on the block. Agentic AI has seen a steady rise in search results, particularly in the last quarter of this year.

This may be linked to companies such as Accenture and Nvidia announcing joint plans to accelerate agentic AI adoption (as well as Honeywell and Google Cloud).

Unlike traditional AI that merely responds to prompts, agentic AI autonomously creates workflows and acts based on user intent.

See worldwide search results for ‘agentic AI’ below.

OpenAI closed a $6.6 billion investment round

OpenAI secured a groundbreaking $6.6bn in its latest funding round, hailed as the “largest venture capital deal of all time.”

The fundraising valued the creator of ChatGPT at $157bn following its announcement of plans to transition to a for-profit structure within the next two years.

Notable investors included Microsoft, Nvidia, SoftBank, Fidelity, Altimeter Capital, Khosla Ventures, MGX, and Thrive Capital.

Microsoft accused Google of a campaign to mislead the public and cloud regulators

In a Big Tech spat, Microsoft claimed Google initiated a covert campaign to “discredit” Microsoft and “tilt the regulatory landscape in favour of its cloud services.”

In a blog by Microsoft’s deputy general counsel, Rima Alaily, he stated that Google was about to launch a lobby group with a handful of smaller European cloud providers.

Alaily claimed that Google planned to remain a “backseat member” and allow the other cloud providers to be the group’s face. Still, one firm that chose not to join told Microsoft that the group’s purpose was to criticise Microsoft’s practices in Europe.

UK tech provided mixed reactions to the new government’s first budget

The UK’s new Labour government released its first budget statement, which included increased taxes for employers, an uptick in public spending, and a renewed commitment to focus on growth.

November: US Presidential Election Shakes Tech Sector

Trump vs Harris: key tech policies in the US presidential election

As the US presidential election approached, TI covered the key tech policies proposed by the Republican and Democratic parties.

These included AI and automation plans, such as Trump’s push to minimise AI regulation and Harris’s focus on promoting ethical AI use.

Both parties emphasised strengthening cybersecurity and taking antitrust actions against monopolistic companies.

However, they differed on cryptocurrency: Trump advocated for limited regulation to position the US as a crypto hub, while Harris supported stronger regulation to secure crypto markets and protect consumers.

What does Big Tech stand to gain or lose under a second Trump presidency?

Trump won the US presidential election, and TI analysed the pros and cons of a Republican party for Big Tech.

For instance, Trump threatened to impose 60-100% tariffs on goods from China, which could heavily affect companies such as Apple and Tesla. These companies depend heavily on continued access to the Chinese market and supply chains.

On the other hand, lighter regulation may benefit sectors such as crypto.

Air fryers may be secretly sizzling data

When you threw those sweet potato fries into the air fryer drawer, did you consider that your data may have been stolen in the process?

Consumer rights watchdog Which? warned shoppers that air fryers and other electronic products made in China may collect unnecessary data and share it with third parties.

According to Which? the Xiamoi app, which comes with smart air fryers like Xiaomoi, Cosori, and Aigostar, was linked to ad trackers on platforms such as Facebook and Tencent.

It also requested gender and date of birth when users set up an account, which it reportedly shared with servers in China.

Coca-Cola’s AI-generated ‘Holidays are coming’ ad sparked debate

Coca-Cola’s annual fleet of trucks appeared on our screens — except this time, the entire ad was AI-generated.

The ad sparked controversy online, with one X user calling it “soulless garbage.” It was produced by three AI studios, using generative AI models Leonardo, Luma, Runway, and Kling.

Two subsea cables were severed in the Baltic Sea

Two subsea cables connecting Germany with Finland and Lithuania with Sweden were severed over the course of one weekend.

While the cause remained unknown, Finnish state-controlled cybersecurity and telecoms company Cinia stated such an event does not happen “without an outside impact.”

Neither of the incidents affected internet traffic, as other subsea cable routes were available.

December: The Law Denies Big Tech’s Appeals

A US judge rejected Elon Musk’s Tesla pay package

Elon Musk’s four-year-old child (X Æ A-12) may not get so many presents this Christmas, as a Delaware judge upheld her decision to void his $56bn Tesla pay package.

The judge ruled that the car manufacturer’s board of directors failed to act in the best interests of shareholders when devising Musk’s 2018 compensation deal. She cited conflicts of interest and material misstatements made to investors.

ABBA’s Björn Ulvaeus warned of AI in the music industry

A study by the International Confederation of Societies of Authors and Composers (CISAC) found that human creators are “set to lose billions” due to GenAI.

Abba’s co-founder and president of CISAC, Björn Ulvaeus, responded to the report by warning that poorly regulated AI has “the power to cause great damage to human creators, to their careers and livelihoods.”

The CMA approved the £16.5bn Vodafone and Three deal and set terms for UK telecom’s future

The British telecoms sector saw a significant milestone as the UK Competition and Markets Authority approved the merger of Vodafone and Three, paving the way for a £16.5bn ($21bn) alliance.

The deal required several legal obligations, including a commitment to spend £11bn ($14bn) improving 5G connectivity services nationwide. (London is rated one of the worst capital cities in Europe for 5G connectivity). The deal brings together the UK’s fourth and third biggest operators.

A federal court upheld a ruling on TikTok forcing it to sell or face a US ban by 2025

A federal appeals court supported its decision requiring TikTok’s Chinese partner company, ByteDance, to sell its US operations or face a nationwide ban. It has until 19 January 2025 to comply with the ruling. If it fails, the app could be disabled for 170 million American users.

However, TikTok has vowed to appeal the decision to the Supreme Court, arguing that the law infringes on free speech rights and unfairly singles out the platform.

Google unveiled a quantum chip

Finally, as a holiday gift, Google unveiled its quantum chip, Willow. It said that the chip could perform a standard computation in under five minutes, which would take today’s fastest supercomputer an inconceivable amount of time (ten septillion years).

Google Quantum AI’s founder and lead, Hartmut Neven, added that the new chip moves the firm “significantly” toward commercially relevant applications.

Missed the rest of the year? Read our roundups of Q1, Q2, and Q3 to catch up.

The post Q4 Wrapped Up: the top tech stories of October to December 2024 appeared first on TechInformed.

Over the past few months, we’ve gathered insightful clips from various tech voices, answering one poignant question: “What are your 2025 tech trend predictions?”

We cover the direction of AI applications, green tech and sustainability developments, payment solutions, HealthTech advancements, the pervasive threats of cybersecurity, and more.

Watch here to find out which predictions from last year came true; TI:TALKS — 2024 Tech Predictions

The post TI:TALKS — 2025 Tech Predictions appeared first on TechInformed.

Recent stats state that AI has the potential to unlock £119bn annually in revenue through driving productivity. However, this potential can only be fully realised if the technology gains acceptance from all levels of an organisation, especially from grassroots employees who are, understandably, concerned about its impact on their jobs.

The pressing question then becomes: How can employers alleviate fears around AI while fostering a culture of trust and innovation? It’s a delicate balancing act and HR is uniquely positioned to lead the way.

Innovation vs employee well-being

When it comes to introducing AI into the workplace, openness and transparency are non-negotiable. Employees are naturally wary of the impact AI might have on their job security, and as HR professionals, we need to front-load communication with honesty. It’s essential that employees see leadership as genuinely considering the broader impact of AI and not just the bottom line.

The role of HR is critical here. We are the conscience of the business, often reminding leadership of the people impact while balancing financial goals. It’s not a matter of asking, “Should we be adopting AI?” but rather, “How do we implement AI in a way that’s beneficial for everyone?” AI should not be framed as a replacement for people but as a tool to enhance their work.

By automating tedious, repetitive tasks, we free up employees to focus on more strategic and creative endeavours. Jobs are evolving, not disappearing, and it’s HR’s role to highlight this evolution. Our message to employees should be clear: AI is here to support you, not to sideline you.

In some cases, AI will inevitably replace certain roles or reduce the need for as many people in highly repetitive areas and it’s HR’s responsibility to communicate this honestly, ensuring employees understand the evolving nature of work. Our message should be clear: AI is here to support growth and efficiency, while reshaping roles, not always replacing the value people bring.

Trust through engagement

National surveys often reveal many employees believe AI will lead to fewer jobs, but two-thirds of employees believe it won’t replace them. This indicates a level of optimism, but there’s still underlying anxiety. Employees worry about using AI in their day-to-day roles, fearing they might be judged for leveraging technology to lighten their workload.

The key to addressing this anxiety is in how HR managers can build trust. By highlighting the benefits AI brings – such as space for increased productivity, creativity, innovation and necessary thinking time – we can shift the conversation from fear to empowerment.

It’s about creating meaningful roles that engage employees and ensure they continue to feel valued. Part of our job is to reskill and retrain the workforce to adapt to AI. This doesn’t mean we take responsibility for every employee’s learning journey, but we must actively understand how AI is affecting job roles and where support is needed.  By doing so, we create a workforce that feels equipped and empowered to work alongside AI, rather than being overwhelmed by it.

Redefining the role of HR

HR’s role is evolving alongside the technology we manage. It’s no longer just about managing people; it’s about managing change. We need to take a proactive stance in helping employees see AI as an ally. This means taking the stigma away from “just sitting and thinking” or using AI for initial ideas. Employees often feel guilty if they’re not constantly busy, but some of the best insights come during those moments of reflection.

AI can help employees carve out time for creativity by automating routine tasks, but HR needs to guide this process carefully. We must avoid the risk of lethargy and complacency. AI should be a tool that sparks innovation, not one that leads to laziness. Encouraging employees to use AI to kickstart projects, but not relying on it for everything, helps maintain a balance between human creativity and technological efficiency. I believe that both HRs and management should share how they integrate AI into their everyday work to alleviate the worry and doubt about using the technology in their own projects.

HR also has a responsibility to create guidelines around the use of AI in the workplace. By understanding AI’s role in enhancing work, we can spot when it’s being used inappropriately and intervene to support employees in using it effectively. Usually, it’s the different tone of voice that stands out in an AI generated piece of work and it’s up to the employee’s line manager or HR manager to offer guidance in how to integrate their own personality and tone into their AI generated projects.  These learnings will ensure that AI is seen as a tool for job enhancement, not job replacement, and protects the integrity of the work being done.

Steps for embracing AI

One practical step HR can take is to embed discussions about AI into the employee experience from the start, including during recruitment and appraisal processes. By making AI part of the conversation from day one, we can remove the mystery and anxiety around it. This transparency ensures employees know what is expected of them and how AI will play a role in their day-to-day responsibilities.

The role of HR is to ensure that AI is used responsibly, both by employees and leadership. It’s a collaborative effort, one that involves every stakeholder in the organisation. Empowering the workforce, regulating AI’s use and fostering an environment where AI is viewed as a tool for growth rather than a threat are key to a successful AI integration.

From HR to the future

HR professionals themselves need to be prepared for the shifts AI is bringing. Job design is changing, and we must adapt by incorporating AI-related skills into job descriptions and creating new roles that align with this new era. By staying ahead of the curve and understanding AI’s potential HR can lead the organisation through this transition smoothly.

AI is here to stay and its impact on the workplace will only grow. However, by approaching its implementation with openness, transparency and a focus on employee well-being HR can ensure that AI becomes a tool for empowerment rather than a source of fear.

Our role is to bridge the gap between leadership’s excitement and employees’ concerns while fostering a culture where AI enhances, rather than diminishes, the human element of work.

The post The HR’s guide to supporting employee use of AI appeared first on TechInformed.

Her core research interest is the development of Neuromorphic Computing – a nascent technology inspired by the efficiency of the human brain, with potential applications in AI, autonomous vehicles, healthcare, and space exploration.

Over the course of our chat Majumdar claimed that this next generation of intelligent and adaptive computing and sensing also offers significant energy savings and more effective real-time decision-making, and that the smartest, most efficient LLMs are to be found in nature rather than code.

Majumdar also talks about the joys of being an international scientist and the benefits of the Finnish system, which has enabled her to conduct academic research while raising a young family.

When did you land in Finland?

My husband got a post-doctoral position in Turku when my eldest son was a few months old. We lived there for about nine years, so it will always hold a special place in my heart.

In the beginning I thought ‘let’s take some time off’ but it was quite isolating being on my own all day, so I started looking at options and through the university there I managed to get a scholarship sponsored by a private foundation – which funded my first research project.

What do you like about researching and working in Finland?

The independence you are given worked well for me as a young mother. No one interferes in anything, it’s a very trust-based system. You know your responsibilities and you know what needs to be done. When my son was sick, I was not in the lab, but when he was fine, I worked during my weekend. That kind of flexibility was helpful, and the supervisors were also supportive.

Another thing is that the childcare support is incredibly good. When I dropped my son off at daycare, I didn’t even worry about what he was doing. That’s something I think in those initial years, helped a lot.

What is neuromorphic computing?

It is about making computing more human-centric and studying also how the human brain processes data.

The human brain works completely differently to a computer’s and this requires a complete paradigm shift. The way current computers run means that the AI algorithms are very power hungry. And that’s because these computers were not designed for this kind of task. AI depends on a huge amount of data – billions of data sets – to make it understand what the correct answer or action is.

But humans, and even the smallest of insects, are good at certain things without any specific training. Take one small insect, the navigation path, or the collision avoidance path they have, it’s hard to replicate that in drones or in current machines.

It sounds like our brains are a lot more efficient that ChatGPT!

The human brain works in spikes whenever an event occurs, whereas computers transmit stuff all the time to the cloud which is a lot less efficient and more energy intensive.

So, a 24/7 surveillance camera. Or a health monitor. When there is nothing happening, a computer will continuously transmit data to cloud just not knowing what to look out for because there’s no ‘local intelligence.’

To imitate biological intelligence, the chips need to be more localised – you need to put them closer to the sensor so that it only communicates the relevant data to cloud, allowing it to work more efficiently.

With arrhythmia detection, for example, personalised trained chips can do 24×7 heartbeat monitoring of patients and can do anomaly detection at a much lower power and communication bandwidth cost than the current systems.

Besides healthcare and security surveillance, are there other applications?

Autonomous cars are another. Anywhere where you need chips to integrate and process data from multiple sensory sources simultaneously. Neuromorphic systems can adapt and “learn” from scenarios, improving their functionality over time.

For instance, if a car’s sensor when it is foggy or there is low visibility, the system can compensate by relying on data from other sensors, through associative learning, to make a safer judgement.

In space exploration, its use is also being actively being discussed. Space missions often have limited power sources, such as solar panels. Neuromorphic chips consume far less power than traditional processors, making them ideal for energy-constrained missions.

So, when Mars is at its farthest distance from Earth it takes more than 50 minutes to communicate in one direction so a simple instruction could take two hours. Chips that enable localised, event-based decision-making without the need for constant instructions from Earth, could be critical for autonomous operations in space.

You referred to a 2019 report that said training a single AI model takes up the same amount of carbon as five cars during their lifetime. What does this mean for the future of LLM development?

And that report was published in 2019 – the power demand from LLMs like GPT-4 are increasing exponentially.

The problem is that so far, we can actually keep up with these energy demands, but what will be challenging is when the hardware cannot keep up – in five-or ten-year’s time.

Moore’s Law – which states that the number of transistors on a chip doubles every two years while costs halve – is widely considered to be nearing its practical limits due to physical constraints in semiconductor fabrication. We simply cannot get these chips any smaller or squeeze more onto them.

The artificial intelligence we are seeing today is coming from the software side but if the hardware cannot give enough support to the software when AI workload magnifies enormously, then things will go very wrong.

How much energy would we save using neuromorphic computing?

Individual components wise: they can save a million-fold energy compared to current devices. But then we are still not able to switch fully to new technology. We are currently working towards a hybrid model.

You say there’s a need for innovation not only from device level but also in architecture for hardware support…

Algorithms need to understand the new devices because the ones we are using are based on old hardware. So, if the new algorithm can exploit the full potential of the new hardware, the system could become more efficient.

Are you investigating partnerships in this area?

Yes, in the US we have projects with the University of Massachusetts (UMAS) where they are doing pressure sensor-based computing. There are also other European projects. But hardware fabrication is expensive – you can spend billions on chip design and development – it’s very resource hungry.

Given how expensive it is, shouldn’t enterprises be more involved?

The big players are there- IBM, Intel, Samsung – they are running activities in this direction, but it is very good to have collaboration between industry and university together. It is not a mature technology yet, but it is coming….

What do you enjoy most about your job?

The best thing is nothing is repetitive, it’s something new all the time and it is always something challenging that you need to solve a problem. Also, getting to know so many very brilliant people and having the opportunity to work with the most brilliant minds. It is the human connection – you get to know so many people, their stories and how and why they chose this field. It is nice.

What do you do to relax, and switch off from work?

I enjoy listening to music. I used to be a singer a long time ago. My mother was a very good singer, and she trained me, mostly in songs from our Calcutta heritage. And when I am stressed or sad I find myself back in those words and connected to them. They are a vastly different collection of songs on many different topics, some of them are on nature, love, spirituality. They have the power to touch you.

How do you take your coffee (or tea)?

I am a very big tea fan. I come from the land of Darjeeling, and it is my favourite morning tea. Luckily in Europe now there are lots of sellers. I make it with loose leaves, the traditional way. No milk, no sugar.

Read more here: Will neuromorphic-controlled robots soon become a reality?

The post A coffee with… Sayani Majumdar, Associate Professor, Tampere University appeared first on TechInformed.

Enterprise leaders across verticals want to harness the power of AI to improve efficiency, extract data-driven insights, and drive positive business outcomes.

While AI tools are indeed on the path to delivering value to many organisations, the increased visibility around this quickly evolving category exposes another by-product of AI usage: elevated organisational risk.

Recognising this risk has spurred several global regulators and lawmakers to action. One prominent example is the directives the US government outlines, which aim to ensure a safe and sustainable path forward for government-facilitated AI efforts.

Big tech’s closed AI ecosystems are hindering trust and development, report claims

On October 30, 2024, the White House issued the Executive Order on Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence, a framework designed to guide US federal agencies as they adopt AI-powered capabilities.

The AI Executive Order was notable for its depth and clear directives, including specific calls to action for more than 20 agencies. Implementation deadlines spanned between 30 and 365 days.

As we examine the AI landscape one year after this directive, the progress made, including the recently released National Security Memorandum on Artificial Intelligence, is encouraging.

While these actions effectively establish the baseline expectation that privacy and security cannot be afterthoughts when adopting AI but must be intentionally integrated into AI systems from the beginning, one action-filled year is not the end of the story.

It is important to continue this commitment to creating an environment where AI risks are acknowledged, privacy is respected, and security is foundational.

At its core, Secure AI is about minimising risk and enabling trust and security while enhancing decision-making, protecting privacy, and combating risks.

To deliver the best outcomes, AI/ML capabilities need to be trained and enriched using a broad, diverse range of data sources.

Privacy-Enhancing Technologies

Foundational to these efforts are Privacy-Enhancing Technologies (PETs), a family of technologies uniquely equipped to enable, enhance, and preserve data privacy throughout its lifecycle.

PETs allow users to capitalise on the power of AI while mitigating risk and prioritising protection.

Data is the foundation upon which AI is built, so it may seem obvious that the privacy and security challenges that have long been associated with data also extend to AI tools and workflows.

Yet, within many organisations, the fog of AI hype seems to have hidden this reality. Since the surge of activity driven by the host of Generative AI tools that burst onto the scene in late 2022, numerous AI efforts have advanced without a passing thought to the security implications or long-term sustainability.

Responsible AI innovation requires action — and systemic action requires resources.

Like the AI Executive Order directives that initiated a number of workstreams in the US, there remains a role for global governments to work alongside industry to support safe, responsible, trustworthy, and sustainable AI practices.

Technical AI experts from nine countries and the European Union will soon meet in San Francisco to discuss international cooperation on AI safety science through a network of AI safety institutes.

Legislative and regulatory actions and the funding of tools and technologies that prioritise privacy and security further bolster global AI leadership.

Dedicating resources to adopting technology-enabled solutions, such as PETs, will help ensure that the protection of models and workflows is foundational, safeguarding the vast amount of sensitive data used during AI training.

Reflecting this pursuit, the European Union approved the EU Artificial Intelligence Act in March 2024. This consumer-centric act mandated the right to privacy by stating that personal data protection must be guaranteed throughout the entire lifecycle of the AI system.

“Measures taken by providers to ensure compliance with those principles may include not only anonymisation and encryption but also the use of technology that permits algorithms to be brought to the data and allows training of AI systems without the transmission between parties or copying of the raw or structured data themselves.”

The NCSC Guidelines for Secure AI System Development were released in the UK in November 2023.

They identified security as a core requirement, not just in the development phase, but throughout the life cycle of the system and pointed to PETs as a means of mitigating risk to AI systems: “Privacy-enhancing technologies (such as differential privacy or homomorphic encryption) can be used to explore or assure levels of risk associated with consumers, users and attackers having access to models and outputs.”

Sustaining momentum

As the AI market continues to expand exponentially, leaders must understand and support efforts to drive the responsible use of these technologies.

That support includes crafting directives, policies, and budgets to advance Secure AI efforts. It also includes working with tech leaders, academics, and entrepreneurs who have a strong stake in advancing the adoption of these technologies in a secure and sustainable way.

Prioritising the safe, secure, and responsible use of AI and providing the funding necessary to sustain its advancement will ensure the impact of these transformative tools far into the future.

The post Trustworthy AI: one year after the Executive Order appeared first on TechInformed.

No technology topic was discussed more at major tech conferences, in press releases, or even by politicians than artificial intelligence, especially the various forms of GenAI and large language models.

We’ve seen a whole host of new AI launches, with Cisco, Salesforce, and even Amazon jumping aboard the AI train. Meanwhile, industry leaders such as OpenAI, Microsoft, and Google have all rolled out new products and unveiled new partnerships.

There were also signs of a shift in AI technology as more and more firms revealed “agentic” models—AI agents designed to serve users by automating mind-numbing processes or handling elements such as customer services.

Three years after the public launch of ChatGPT overturned our understanding of AI, it doesn’t appear to be losing momentum… meaning 2025 could bring even more exciting developments.

When the chips are up

Perhaps no other tech company has had a better year than chipmaker Nvidia, which has positioned itself at the forefront of the AI revolution.

Once a relatively modest chipset maker known for its graphic processing units (GPU), Nvidia has metamorphosised into one of the world’s most valuable public companies.

It has partnerships with all the big AI players, including Google, Microsoft, and OpenAI, and the company’s value has almost doubled in the last 12 months.

Can Nvidia’s incredible success last? Several factors favour leather jacket-wearing enthusiast CEO Jensen Huang and his firm. This year, Nvidia unveiled its new computing architecture, Blackwell, which is specifically designed for AI, positioning it to benefit even further from the AI boom.

However, one negative is on the horizon — China has just announced an antitrust probe in an escalation of its tech war with the US.

Connecting the world at the Olympics

2024 was a massive year for major events, including the UEFA European Championships in Germany and a spate of major elections worldwide. However, no event was bigger than the 2024 Olympic Games held in Paris over the summer.

A record-breaking 12.1 million tickets were sold for the Paris Olympics and Paralympics, which saw athletes compete in more than 329 events across 32 sports in a three-week stint.

Logistically, the games were a huge challenge for the organisers of the International Olympic Committee and the French Government.

The event got off to an auspicious start when a sabotage attack damaged several rail networks. Though these were denied, there were also reports of blackouts and attacks on telecom infrastructure.

Deepfakes and cyber-attacks: How the Paris 2024 Olympics became a hotspot for digital warfare

Orange, the IOC’s broadcast and connectivity partner, supported the entire event. Orange provided a private 5G network throughout Paris to power the games.

The 5G network provided capacity across 32 spots and 120 official sites across the city and was made available for broadcasters and teams on the ground, as well as spectators visiting Paris.

According to the telco, around 20,000 photos were transferred on its network in the first week of the Games alone.

Orange also supported the opening ceremony by providing 5G smartphones, which were used to live broadcast the parade down the River Seine.

The French incumbent has since revealed a partnership with the French postal service to give new life to network equipment used during the games.

Beginning in 2025, around 90% of the Wi-Fi terminals and 78% of the switches from the Olympic sites will be refurbished and installed at La Poste’s locations in France.

Musk ado about nothing

A controversial pick now — and they don’t come much more controversial than Tesla owner, SpaceX boss, and soon-to-be US government consultant/DOGE chief, Elon Musk.

To say it has been an outright fantastic year for the billionaire wouldn’t really be accurate — no single person in tech has generated more headlines than Musk in 2024, though not all have been positive.

Musk has certainly faced numerous challenges, including questions about his proposed pay, the performance of his social media platform Twitter/X, and disputes with regulators in regions from Brazil to Europe.

However, one major decision looks set to pay off handsomely: his call to throw his considerable might behind Donald Trump’s re-election campaign.

For Musk, Trump’s win in November means he is now arguably one of the most powerful non-politicians on the planet. The incoming President is set to hand him his own department (DOGE) tasked with reducing governmental waste.

Musk remains the world’s richest man, but according to Fortune, his net worth was buoyed by Tesla’s growth (up around 37%) and success at SpaceX.

Speaking of SpaceX, Musk’s rocket company continued to push the boundaries of space exploration technology with the sixth flight test of Starship last month. At the same time, its Polaris Dawn mission saw the world’s first privately funded spacewalk.

With Trump due to return to power in January, this year could just be one small step for his billionaire best friend.

Reaching for the Bluesky

As we already mentioned, not everything went Elon Musk’s way, and our final tech triumph in 2024 is for a company that tried to capitalise on — and seemingly succeeded in — some of Musk’s misfortunes.

Elon may be looking beyond the clouds with his space exploration, but it’d be remiss to ignore the sky… Bluesky, that is.

Created in 2019 by founder Jack Dorsey, previously of Twitter, Bluesky has quickly become the alternative microblogging platform to Musk’s X — or the home of the ex-Xers, so to speak.

Bluesky launched as an invite-only service in February 2023 and opened registrations in February 2024. However, the platform’s growth skyrocketed around the US Presidential Election as users sought an alternative to X.

Today, Bluesky has around 25 million registered users and has more than tripled its user base within the last three months.

Though it is still way behind the former Twitter’s estimated 600 million monthly users, Bluesky could position itself as a true alternative to Elon Musk’s platform in a way that previous rivals, such as Threads, have failed.

You’ve read about the tops, now read the bottoms: the top tech turkeys of 2024!

The post 2024’s Top Tech Triumphs: AI Domination, Nvidia’s Rise, and Musk’s Mixed Year appeared first on TechInformed.

At a glance…

• • ✦ Meta and OpenAI expanded their AI offerings to the world
• ✦ The threat of AI shook governments around the world into action
• ✦ Sustainability: Poo-powered planes to the rescue!

April: Earthquakes and Space Grapes

Amazon cuts hundreds of roles at AWS

Amazon Web Services announced plans to axe hundreds of jobs across sales, marketing and global services. The plans were revealed in an email sent to staff, as executives said the cloud company was to shift its focus to self-serve digital training and training programs run by external partners.

AWS senior vice president Matt Garman said, “The changes we are making are preparing the organisation for the future, aligning with our strategy and priorities, and reducing duplication and inefficiency.”

Amazon also announced it would be ditching AI-powered checkouts in the US.

Meta released its AI service, Llama, to the public

Meta released Llama 3, an advanced AI model that claimed to be more powerful than OpenAI’s ChatGPT and Google’s Gemini. It featured significant upgrades, including reasoning abilities, multilingual support, and multimodal potential, driven by its 8B and 70B parameter models—seven times larger than its predecessor, Llama 2.

Integrated with Meta AI, it became accessible on Instagram, Facebook, and WhatsApp in the US. In the same month, OpenAI released its voice engine to select partners.

UK Space Agency awards grant to grow food in space

The UK Space Agency granted agritech firm Vertical Future (VF) £1.5 million to advance its mission of taking vertical farms into outer space.

VF, a UK-based specialist in vertical farming technology, initiated the second phase of its Autonomous Agriculture for Space Exploration project. It is adapting its Earth-based controlled-environment agriculture (CEA) systems for Low Earth Orbit (LEO), which is expected to launch in 2026.

VF’s project, part of the UK Space Agency’s £20 million International Bilateral Fund, aimed to expand its CEA systems to the Moon and Mars in the 2030s.

Chip plant evacuations follow strong Taiwan earthquake

Taiwan Semiconductor Manufacturing Co (TSMC), a key supplier for Apple and Nvidia, evacuated several fabrication plants following a powerful 7.2-magnitude earthquake in Taiwan. The quake, the strongest in 25 years, struck the eastern province of Hualien, claiming seven lives, injuring 700, and leaving 77 trapped in tunnels.

Taiwan, responsible for producing 60% of the world’s semiconductors, faced significant global supply chain risks when its fabs were affected, as seen during the COVID-19 pandemic.

In the same month, just across the East China Sea, South Korea pledged to invest $7 billion in AI to retain its edge in chip manufacturing.

May: AI Deepfakes and Cyber-Attacks

An ad agency boss was the target of a deepfake scam

Mark Read, CEO of advertising giant WPP, was targeted in a sophisticated deepfake scam. Scammers used a fake WhatsApp account with Read’s publicly available image to initiate a Microsoft Teams meeting with a senior WPP executive.

During the call, they employed a voice clone and YouTube footage of Read, impersonating him in real-time to request sensitive information and financial actions.

The attempt failed due to the vigilance of WPP staff. In an email, Read warned employees about evolving cyber threats and urged them to be cautious of suspicious requests involving money, passports, or “secret” transactions.

Expedia unveiled a travel buddy AI app for US customers

Expedia has unveiled Romie, an AI-powered travel assistant, along with additional features at its Explore event in Las Vegas.

Romie’s capabilities include learning travellers’ preferences for activities, food, and accommodations, integrating into group trip planning chats, summarising discussions, and making suggestions. The app also extracts travel details from emails and recommends nearby restaurants or activities during trips.

Expedia also extended AI-powered tools to partners, including personalised itineraries, price comparison tools, and guest review summaries for app users in the US.

UK Ministry of Defence hit by major cyber-attack

The UK Ministry of Defence’s payroll system, managed by SSCL, was hacked, exposing sensitive data of 270,000 armed forces personnel, including names, bank details, and addresses. While Whitehall sources suggested Chinese involvement, the government did not officially name a perpetrator, and China denied any role.

Defence Secretary Grant Shapps announced an eight-point response plan, including system security measures, investigations, data monitoring, and a helpline for affected individuals. No operational data was compromised, but the breach raised concerns about supply chain vulnerabilities.

Global AI regulation efforts prompted US-China talks

The US and China convened in Geneva to discuss artificial intelligence’s risks and governance challenges, focusing on security and ethical concerns. US Secretary of State Antony Blinken and China’s Foreign Minister Wang Yi addressed misunderstandings and explored global AI norms despite competitive tensions.

Experts emphasised the importance of cooperation, highlighting the need for privacy, fairness, and adherence to regulations for AI to succeed globally. However, trust issues and safeguarding strategic sectors like healthcare and energy remained critical barriers.

Did the FBI misidentify the leader of Lockbit?

The FBI and the UK’s National Crime Agency identified Dmitry Khoroshev as the leader of the ransomware gang LockBit following a cyberattack on the group earlier in the year. Khoroshev was sanctioned and banned from travelling to the US, UK, and Australia. He denied the allegations, claiming to have no connection to the gang.

LockBit dismissed the claims, offering a reward to confirm Khoroshev’s well-being. While experts were uncertain if the FBI correctly unmasked the leader, they believed Khoroshev was connected to the group.

June: Self-Driving Taxis in San Fran, plus the NHS Got Hacked

Ransomware gang leak 400GB of NHS data from London hospital hack

Hackers from the Russian gang Qilin leaked nearly 400GB of sensitive patient data stolen during a ransomware attack on Synnovis, an NHS blood testing partner. The attack disrupted pathology services across London hospitals, delaying over 3,000 appointments and operations.

Despite demands for $50 million, Synnovis and NHS officials refused to pay. The leaked data reportedly included patient names, dates of birth, and blood test results.

Elon Musk’s SpaceX was hired to decommission the International Space Station

NASA awarded SpaceX a contract worth $843 million (£668 million) to safely decommission the International Space Station (ISS) early next decade. SpaceX will develop a de-orbit vehicle to guide the 430-tonne station into Earth’s atmosphere, ensuring a controlled descent to Point Nemo, a remote Pacific location.

Operational since 2000, the ISS remains structurally sound, but NASA aims to prevent uncontrolled re-entry. After the ISS’s retirement, the agency will focus on commercial space stations and the Lunar Gateway project, a moon-orbiting platform.

Nvidia was named the world’s most valuable listed company (again)

Nvidia leapfrogged Apple and Microsoft to become the world’s most valuable listed company, driven by the AI boom. The American chipmaker’s share price hit an all-time high, with the company valued at $3.34tn (£2.63tn) at the time — almost double the value at the start of 2024.

Apple partnered with ChatGPT for AI integration in iPhones

Apple unveiled “Apple Intelligence” at its Worldwide Developers Conference, integrating ChatGPT into Siri to enhance AI-driven features across iOS, iPad, and Mac devices. CEO Tim Cook emphasised privacy, with local AI processing and minimal data collection.

Siri gained improved context-aware capabilities, while new tools like “Rewrite” and “Proofread” refined text and tone. The event also highlighted the global rollout of the Vision Pro headset.

Waymo made its self-driving taxis available to everyone in San Francisco

Waymo, Alphabet’s autonomous driving company, made its self-driving taxi service available to everyone in San Francisco. After receiving approval from the California Public Utilities Commission, Waymo operated its commercial driverless service 24/7, despite earlier complaints about traffic disruptions.

Previously limited to a waitlist, the service became accessible via the Waymo app. Nearly 300,000 people signed up for rides as the company sought to build public trust in autonomous vehicles. Waymo operated around 300 self-driving taxis in San Francisco, with additional fleets in Phoenix and Los Angeles.

Continue reading — Q3 Wrapped Up: The Top Tech Stories of July to September

The post Q2 Wrapped Up: the top tech stories of April to June 2024 appeared first on TechInformed.

Deep Turnaround is a tool developed by Aviation Solutions, a subsidiary of Schiphol Group, the airport umbrella. It uses AI algorithms, machine learning, and cameras to automatically detect the start and end times of the ground handling processes.

According to the firm, this makes it possible to predict delays.

In its announcement, the company said collaboration between airlines and ground staff, alongside the tool’s live insights, allows for proactive decision-making that was not possible before.

The tool’s rollout has started and is expected to be live at multiple stands in the first quarter of 2025.

“Innovation is a key part of our approach at Edinburgh Airport, and using AI to help improve our turnaround times is something we are very excited about,” said Peter Barnes, head of business transformation at Edinburgh Airport.

“Deep Turnaround’s system and use of technology have the potential to make our operations even more efficient, and we look forward to collaborating with our colleagues to bring this to fruition.”

Caroline Massart, director of Aviation Solutions, added, “The right insights provided by data help make airport operations more predictable.

We’re collaborating with multiple airports on Deep Turnaround, and we’re very proud and excited to add Edinburgh to our community of users.”

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