Spider-Noir: Returning to hard lights for a radical dual-look design

RedShark News

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Spider-Noir, Amazon's Nicolas Cage vehicle, comes in two distinct varieties: moody noir and lush color. The key to pulling off the show's distinctive looks was using dual LUTS and returning to the pre-LED era of lighting tools.

How do you make a show is both exquisite homage to classic 1940s noir simultaneously with one that feels as visually lush in classic Hollywood colour? The cinematographers behind Amazon Prime series Spider-Noir have managed it by leaning into old-fashioned lighting designs and vintage tools.

“Spider-Noir was about completely embracing the look and technology, frankly, of film noir when it was created,” explains Peter Deming, the veteran DP who lensed David Lynch’s neo-noirs Lost Highway and Mulholland Drive.

 “A lot of the lighting units we're using were very traditional lighting that I started my career with in the business that have now sort of taken a back seat to LED lights.”

Rather than relying heavily on modern fixtures, the cinematographers dusted off older equipment, including Mole-Richardson units, Fresnels and other vintage hard-light sources. The result is a dramatic visual black and white style built on deep contrast and sculpted shadows.

“Lost Highway is noir‑ish, but it’s modern. It’s not a hard‑light film,” says Deming, who shot episodes 5 & 6 of Spider-Noir. “Here we’re using hard light, and lighting faces with hard light with a precision and edge that only those sources can produce.

“It was terrifying at first to light faces with hard light again, but then you get the hang of it.”

Darran Tiernan, the Irish DoP who established the grungy look of Gotham for HBO’s The Penguin, was lead cinematographer on Spider-Noir and shot the pilot plus episodes 2-4, 7 & 8.

“LED technology certainly gives you a lot of control and has become the mainstay of modern production but it also sort of pushes you towards softer light,” he says. “It was clear to me that we needed to go back to using older fixtures and rewire my brain accordingly.”

The series was originally conceived to be shot and streamed solely in black-and-white, but on the first day that Tiernan joined pre-production he and the rest of the creative team were asked whether a full colour version was also possible.

“There was a request for a colour version,” recalls Tiernan of a meeting with showrunner Oren Uzeil. “It had to be one that we were really happy with and that meant one that could exist without compromising the noir foundation.”

This triggered an extensive period of testing with colourist Pankaj Bajpai, who developed two LUTs (one monochrome, one colour) applied to the RAW Venice 2 negative.  

Dozens of stills from BW classics like Double Indemnity, The Third Man, Sunset Boulevard, The Killing and The Night of the Hunter were pinned to production office walls alongside early noir themed colour films like Niagara.

“Once we discovered the recipe, everyone was moving in the same direction,” Tiernan says. “We would monitor in black and white, except for focus pullers who required colour. Even before we'd do a take, I'd be flicking between them to see. Within a few days, you get very used to that because this is the way we are creating this world."

Extensive testing became crucial. To ensure consistency, they built a miniature studio where departments could preview fabrics, textures and set elements under the exact lighting and LUTs used on set. FX‑series cameras were supplied to other HoDs for test shoots because, says Tiernan, they have the same colour science as Venice.

Tiernan describes the process as “a constant collaboration, where colour had to be exciting but could never infringe on how good the black‑and‑white looked. We never went into a day of shooting not understanding what something could look like.”

The show’s graphic‑novel origins were equally influential. Spider-Man: Noir first appeared in 2009, as part of the Marvel Noir universe. Tieran studied the original issues and cites executive producers Phil Lord and Christopher Miller’s Spider‑Verse animated film series as a major touchstone. “The angles they chose and the energy in the action sequences were really inspiring,” he said.

He also looked to the stark framing of Richard Stark's Parker: The Hunter a 2009 graphic novel based on the fiction by Donald Westlake about a professional thief which John Boorman translated to screen in 1967 as Point Blank.

Working with storyboard artist Jay Martin, they translated these influences into compositions and lighting designs which Tiernan describes as a hybrid between film noir, comic-book and pulp fiction.

The colour version itself evolved into “a heightened, Technicolor-inspired” interpretation of the noir world. Influences ranged from early colour photography books such as ‘The Colours of Life’ (a book of colourised BW early 20th century stills) and noir cinematographer John Alton’s ‘Painting with Light’ from 1948 to the bold psychological palette of Alfred Hitchcock's Vertigo.

Rather than competing with the gritty monochrome presentation, the saturated colour grade was designed to complement it.

Beginning to grade his episodes, Deming was surprised to learn that Bajpai had barely touched the first pass. “That’s a testament to Kevin Britton, our DIT, who kept such a great eye on the look and would re‑time things within the day so they matched.”

Neither cinematographer altered their creative approach, regardless of which version would ultimately be viewed. “You’re lighting based on the content of the scene,” says Deming. “You’re going for a noir look, and those aspects are in the colour version as well. You’re just shooting the best way to tell the story.”

Yet audiences consistently report different emotional responses. “People say the black‑and‑white feels darker, more dramatic and they’re probably right, despite both editions using identical performances and compositions,” Tiernan remarks.

“Film noir cinematography is really about the psychology of what’s going on, telling the story in a visual and graphic sense. Being allowed to do that is exciting for any cinematographer.”

When AI and virtual reality converge

IEC E-tech

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Artificial intelligence (AI) is enabling extended reality environments (XR) to push boundaries even further. While standards for XR exist, more will be required to foster interoperability between both worlds.

 

Over the last ten years, technologies such as artificial intelligence, machine learning (ML), virtual reality (VR) and augmented reality (AR) have all advanced at a remarkable speed. At the same time, innovations in optics, display engineering, microprocessors and rendering algorithms have helped to create increasingly sophisticated immersive environments. Today, people can explore a wide range of virtual spaces, whether they use a headset or not, from videogames and virtual tours to social platforms and educational tools.

While VR and AR technologies (usually bracketed under XR for extended reality) have developed independently of AI/ML, they are increasingly converging.

“AI can enhance XR in numerous ways,” says Dr Takeshi Kurata, Director, Research Institute on Human and Societal Augmentation, AIST in Japan, and the Acting Chair of the joint technical committee between ISO and IEC,  ISO/IEC JTC 1/SC 24, responsible for work on computer graphics, image processing and environmental data representation. “AI helps create, maintain and update virtual content at a far lower cost than manual methods,” he adds.

For example, when re-creating real‑world environments, human appearances, or objects, generative AI can deliver hyper realistic results at a fraction of the cost of conventional methods. The caveat is that unless checked by human expertise, this can sometimes lead to hallucinations.

How AI can elevate XR

A growing field is augmented intelligence - using AI to enhance human capability rather than replace it. When paired with VR or AR, augmented intelligence could transform creative and industrial workflows.

Nearly every XR application requires onboarding or instructions. Instead of delivering training outside the immersive environment, XR can embed it directly into the experience, much like videogames that teach players through interactive play rather than manuals.

“People learn better when practice is interactive, contextual, safe, and supported by intelligent guidance,” says Donggil Song, Associate Professor of Engineering Technology and Industrial Distribution at Texas A&M University. “One of the clearest examples is the creation of virtual assistants capable of understanding natural speech and offering personalized guidance.” This approach can be extended far beyond application tutorials. When combined with AI techniques such as natural language processing, sentiment analysis and pathfinding, VR becomes a powerful platform for education and skills development.

“XR already gives us immersive learning or training experiences, but AI gives us intelligence inside that experience,” says Song, whose work at EinBrain Lab focuses on combining AI with XR and data‑driven feedback to improve learning and human performance. EinBrain’s flagship project is AlgeVerse, a fully VR, gamified college algebra platform that uses AI-based peer mentors to give the learner guidance, feedback, and suggestions. The project, which is in year one of a three‑year cycle, supports natural communication and is expanding into a multi‑user environment. “Users might not be able to differentiate which avatars are real students and which are AI peer mentors,” Song explains.

The lab has also created a playful VR environment called Prehistoric Protocols to make learning about computer networking more engaging. “Students travel to a [virtual] prehistoric world with cavemen and dinosaurs. Students must teach them using foundational IT concepts,” Song describes.

AI-powered characters in video games

The video-game sector is one of the earliest fields to adopt practical AI in real products. Modern games use AI for world generation, pathfinding, data analysis and player‑experience modelling. One of the most intriguing recent developments is the population of virtual environments with non‑player characters (NPCs) and AI agents. “As it becomes more difficult to distinguish whether entities are controlled by humans or AI, it may eventually become unclear whether a human society actually exists inside the environment at all,” notes Kurata. “From this perspective, I believe AI-driven NPC control is one of the most impactful developments in this field.”

In rural areas of Japan facing depopulation, there are places where large numbers of scarecrows are placed outdoors to ease the loneliness of declining communities. “In a sense, NPCs can be viewed as a virtual counterpart of such scarecrows,” he suggests. “However, NPCs are controlled by AI in the backend, making them far more realistic and interactive, even though their existence is virtual compared with physical scarecrows.”

Challenges include computational resources

Increased adoption of 5G connectivity will accelerate AI-driven XR applications. With high bandwidth, low latency and the ability to connect vast numbers of devices, 5G enables new forms of edge and cloud computing. This could offload heavy processing from headsets, allowing them to become lighter, cooler and more power‑efficient while still delivering richer experiences.

However, integrating AI into VR and AR is not without constraints. AI workloads often demand substantial computational resources, which increases power draw and heat, potentially making headset devices heavier or less comfortable. Research is underway to create more efficient AI‑specific chips and to run AI on low‑power processors, but as AI applications grow more complex, the tension between capability and efficiency is likely to persist.

Kurata says, “Often we see evaluation indicators like accuracy or precision. However, there are often no metrics for energy effectiveness. If we successfully standardize such metrics for industry, competing companies in this space may try to reduce energy consumption as much as possible.”

Other challenges are social rather than technical. Bias is one of the most serious. Any AI system can reflect the biases present in its training data. Speech recognition, for instance, often performs best for accents similar to those of the engineers who built the system—typically male, English‑speaking developers with American, Indian or Chinese accents. Consequently, it is essential to evaluate AI systems to avoid unintended harm or discrimination.

The need for interoperability standards

In addition to metrics and standards relating to the energy efficiency of these converging systems, the field urgently needs national and international standards for interoperability purposes, according to many practitioners in the field, including Song. “Developing for multiple headsets is easier than before, but still requires significant work,” he says. “Standards reduce friction and improve interoperability, safety, reliability and quality assurance.  If we have strong standards between AI and XR, compatibility and interoperability can be solved. Then more research and more products become possible.”

A foundational step is to agree on XR-related terminology without which, Kurata argues, there will be no standards and no future.

Terminology is where it all starts

Kurata’s argument, outlined in an IEEE paper, is that when concepts span multiple domains, such as AI, XR and the Metaverse, ambiguity in terminology often leads to misunderstanding and hinders effective collaboration.  “Much like technical interoperability in software and systems, the clarification of terminology facilitates semantic interoperability, which serves as a foundation for cooperation among diverse stakeholders,” he states.

The term XR is currently widely used as an expression encompassing VR, AR, and MR. However, there is no clear consensus regarding its origin or meaning.  “XR is sometimes explained as an abbreviation for Extended Reality, but multiple interpretations exist regarding its etymology and formation process,” Kurata writes in the paper XR is XR: Rethinking MR and XR as Neutral Umbrella Terms published earlier this year.

He suggests that XR functions as a “neutral symbolic label” by encompassing multiple “reality”-related terms. Stable usage of such terminology requires governance through collaboration among academia, industry, and standardisation organisations, he insists.

What standards are in the pipeline?

Kurata points to two XR-related standards currently under development that have a strong relevance to AI. The first, ISO/IEC AWI 26073, covers spatio-temporal mixed and augmented reality experience description (MAR-ED) for interactive playback

“MAR-ED is highly compatible with AI because it represents experiences semantically through meaningful events, interactions, and narrative structures rather than only raw spatial or visual data. This enables AI agents or AI avatars to understand, adapt, and dynamically interact with immersive experiences, including adaptive playback and real-time branching. In this sense, MAR-ED can also serve as a semantic experiential framework for AI-driven XR and metaverse applications.”

Related work categorized under document ISO/IEC CD 25767 specifically focuses on avatar face representation for XR communication. It aims to standardize the human-to-3D avatar face modelling process, tailored for users of XR glasses. Kurata says this work is highly relevant to AI because realistic avatar face generation and real-time facial animation rely heavily on AI-based face tracking, expression recognition, and generative modelling technologies.

As both technologies increasingly merge, more standards will be required. IEC and ISO are on the case.

 

Boosting the energy efficiency of data centres

IEC E-tech

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The exponential rise of artificial intelligence (AI) demands a rapid growth in innovative power solutions to store and process data more sustainably and efficiently. The IEC provides the standards required.

AI-powered virtual assistants require ten times (2,9 watt-hours) more electricity to run a query than traditional search engines (0,3 Wh), according to the International Energy Agency (IEA). Multiply that many times over for the data crunched by big tech and start-ups seeking to develop AI and apply it on an industrial-scale and it is easy to see why the race for artificial intelligence is also a race for energy.

Power is an issue…

If, as many believe, AI is the engine of our economic future, then the means to power it must be prioritized by governments worldwide. In turn, the acceleration in demand for AI is leading to greater power density in data centres, the facilities housing the servers, storage systems and networking equipment used to train large language models (LLMs).

The IEA estimates that data centre (DC) electricity consumption will grow more than four times faster than the total electricity consumption of all other sectors between now and 2030. US data centres could consume 17% of all electricity in the country by 2030, the Electric Power Research Institute (EPRI) calculates.

Today, an average hyperscale AI DC is capable of consuming upwards 100 megawatts (MW) - as much power as 100 000 homes. That figure is set to be dwarfed as dozens of projects in the multiple gigawatt (GW) range come on stream. Data centres of 1 GW are being built in India; 6 GW in Riyadh, and 10 GW in Louisiana.

…but so is water!

Not only does this surge threaten energy supply across national grids, there are titanic knock-on effects on local water systems. A single 40 MW facility can consume over 1 million tons of water annually for the cooling of electrical components “putting vast amounts of fresh water resource under increasing pressure,” warns the World Economic Forum.

Concern that AI demands could lead to water shortages have been raised in multiple countries including the UK, US and Uruguay. A third of DCs under construction today are projected to face water scarcity in two decades time. Chile has hosted more than 30 DCs over the past decade but there is now a “backlash as datacentres have drained water from drought-stricken wetlands, consuming billions of litres annually.”

There are also concerns about the CO2 emissions generated by these massive facilities. DCs fuelling AI could be forced to invest in sustainable and decarbonized power generation if state governments in Australia and the EU have their way. That means an obligation to invest in renewables and nuclear sources of energy. Another incentive is to reuse excess heat from data centres to heat homes and businesses, according to the EU Energy Commissioner. Improved energy efficiency is becoming imperative together with the increasing resort to decarbonized and sustainable energy to power these mega facilities.

Making data centres more energy efficient

Data centre energy efficiency must shift from optimizing individual components to “optimizing whole systems,” according to Philippe Vollet, Secretary of IEC SC 23K,  a subcommittee which standardizes electrical and electronic energy efficiency devices, for instance for smart buildings. He is also the Chair of the IEC Advisory Committee on Energy Efficiency (ACEE). The committee has published a guide which helps IEC Technical Comittees include energy efficiency aspects in their standards.

Vollet argues that the first and most decisive factor in data centre efficiency is location. Cooling alone accounts for 30–50% of total energy consumption, making climate a fundamental design variable. “A data centre in Norway will never have the same cooling burden as one in Dubai,” he says. Location also determines the carbon intensity of the electricity mix: a facility in France, with its largely decarbonized grid relying essentially on nuclear power, may have a very different footprint from one elsewhere.

“Proximity to the grid matters too; building hundreds of kilometres from a connection point is inherently inefficient,” he says. Cooling remains the “battlefield” of efficiency gains. Traditional air cooling is reaching its limits at around 40 kW per rack, pushing operators toward liquid cooling and now immersion cooling, where components are submerged in dielectric fluid. (For more on liquid cooling read: Data centres to bear the brunt of climate change | IEC e-tech). Vollet describes immersion as “the best way” to remove heat, though it will require updated safety and performance standards as adoption grows.

IECEE, the IEC System of Conformity Assessment Schemes for Electrotechnical Equipment and Components, is also a key enabler for energy efficiency. As one of the world’s most recognized and trusted multilateral certification systems based on international standards, it offers third party testing and certification for a wide range of electrical and electronic products that align with over 3 000 standards. The use of IECEE certificates helps to ensure consistent quality of products and services and facilitate access to international markets by aligning products in any country with global requirements. Its portfolio includes a number of standards for energy efficiency.

It also runs the IECEE Electrical Energy Efficiency (E3) programme, a globally standardized approach to testing and verifying energy efficiency for electrical and electronic equipment, based on IEC International Standards. 

Reusing heat from huge server facilities

A major emerging opportunity is the reuse of heat. Across Europe, pilot projects (such as one in Bulgaria) are feeding waste heat from data centres into district heating and cooling networks. Recycling half of the waste heat from DCscould meet the heating needs of nearly 4 million European households, according to the EU. While data centres are not designed to be energy producers, Vollet sees heat recovery becoming a “strong secondary use” of their energy footprint, with new standards needed to integrate facilities into urban energy systems.

Beyond cooling, electrical architecture needs addressing. “Every conversion step wastes energy, so operators are moving toward higher‑voltage distribution and direct current power, reducing the number of conversion layers. Data centres may also become grid‑flexibility assets, using their large battery reserves to support the grid during peak demand,” Vollet explains.

Metrics and standards are important

Environmental metrics are broadening too. Once dominated by Power Usage Effectiveness (PUE), which is still key, the sector now also tracks water usage (WUE) and carbon usage (CUE). “Harmonized global calculation methods are essential to this effort,” Vollet says.

That’s where IEC Standards come in: ISO/IEC JTC 1/SC 39, the joint technical committee of ISO/IEC working on sustainability, information technology and data centres, offers a range of design and practices for building and managing DCs. These include KPIs for water usage effectiveness (ISO/IEC 30134-9); measuring server energy effectiveness (ISO/IEC 21836); and a methodology to calculate and present the renewable energy factor of a data centre (ISO/IEC 30134-3:2016); while the document ISO/IEC TR 23050:2019 describes the treatment of data centre metrics in circumstances where electrical energy is stored and exported from within the data centre boundaries.

The IEC also plays a crucial role in the achievement of the UN’s Sustainable Development Goals (SDGs) by providing standards that ensure safety, compatibility, and performance across global markets. Of significance here is ISO/IEC TR 21221:2025, a report which describes the delivery of functional, economic, environmental, social, intellectual and personal benefits by AI systems as perceived by their stakeholders. ISO/IEC SC 42 prepares standards in the field of AI and has published a technical report which looks at the environmental sustainability aspects of AI systems, ISO/IEC TR 20226.

The EU is backing efforts to drive a more circular and efficient energy system. It plans to introduce a ratings scheme marking the performance of data centres regarding energy and water use and sustainability. Ironically, AI-based operation and maintenance optimization plays a role here by potentially saving up to €94 billion a year by 2035, according to the EU.  “Regulation and standardization are proven drivers of energy efficiency,” Vollet concludes.

Nuclear energy is becoming a player

Renewables remain the “fastest-growing source of electricity for data centres”, on track to meet half of the demand by 2030, estimates the IEA. Nuclear energy is also viewed as an important source of decarbonized energy and is expected to become even more so over the next decades. Small modular reactors (SMRs) will come on stream helping to double current global nuclear operational capacity by 2050, according to the International Atomic Energy Agency (IAEA).

Pre-fabricated SMRs could be manufactured and assembled far quicker than the average decade it takes for traditional nuclear plants but start-up costs, regulatory hurdles and getting community buy-in remain challenges. However many pundits stress nuclear’s advantages. “Only nuclear energy can meet the five needs of low-carbon power generation, round-the-clock reliability, ultra-high power density, grid stability and true scalability,” argues IAEA Director General Manuel Grossi.

As evidence of demand, one US SMR developer founded in 2019 was recently valued over USD 9 billion with investors including a hyperscaler with which it plans to add 5 GW of new nuclear power by 2039.  Provided there is “stronger government support” there could be more than 1000 SMRs deployed by 2050, with a total capacity of 120 GW.

IEC Standards provide the global framework for the safe use of this energy. IEC SC 45A  is a subcommittee inside TC 45: Nuclear instrumentation, which was set up to develop standards for the instrumentation, control and electrical power systems of nuclear facilities. It cooperates with the IAEA which sets global safety standards for nuclear energy. The subcommittee's standards cover the entire lifecycle of electrical and electronic control systems of nuclear power plants, from design to decommissioning. It has just published the third edition of IEC 61513, which establishes the general requirements for control systems that are important for safety.

Conformity assessment can help floating data centres

Despite obvious technical challenges, floating data centres are emerging as one of the energy efficient solutions to solve both water scarcity and excessive land use problems. Their main advantage is their significantly lower cooling costs (by being surrounded by water) and consequent reduced carbon emissions.

A number of projects are being devised which include plans by a consortium of Japanese companies to pilot a data centre off the coast of Yokohama; France’s first floating DC launched in Nantes, on the Loire River; a floating data centre park in Singapore is due to open in 2028 and a joint venture to develop floating data centre infrastructure has been signed between a US AI developer and a South Korean electronics device maker.

Off the coast of Shanghai an underwater data centre, claimed to be the world’s first, is now in operation. Windfarms on the water’s surface generate the power to run servers 10 metres underwater. According to the project developers, the system reduces electricity drain by 22,8%, eliminates water use, and cuts land use by more than 90%.

An even more ambitious innovation is being developed by a US company focused on harnessing ocean energy for clean power which will drive AI compute onboard. “While traditional wave energy systems tend to be located close to shore so electricity can be sent back through cables, the waves with the strongest and most continuous energy are further out in the open ocean,” says Garth Sheldon-Coulson, co-founder and CEO of Panthalassa. “Capturing energy there effectively could solve a major part of the global energy problem.”

Its floating ‘node’ consists of a large white sphere mounted to a vertical structure extending down below the water's surface. The repeat motion of water inside the tube generates a high-pressure jet of water which is released through a turbine, which spins a generator.

Instead of transporting energy to power a land-based data centre, the idea is that thousands of floating nodes would directly power onboard GPUs with satellite links transmitting data between the nodes and customers. This is one of the project’s Achilles heel, since relying on satellite transfer means dealing with limited bandwidth, signal delays and complications if multiple nodes must coordinate to handle larger AI workloads.

Another is making the transition from experimental to industrial scale marine energy generation. Various marine energy projects exist around the world, some at more advanced stages than others. None yet can claim to be fully commercial. To move into that space, they rely on a strong standardization framework, with specifications developed by IEC TC 114: Marine Energy Conversion Systems and certified through one of the IEC four conformity assessment systems, IECRE, the IEC System for Certification to Standards Relating to Equipment for Use in Renewable Energy Applications. It was established a little more than ten years ago to help provide third party certification and testing services for all power plants producing, storing, or converting energy from wind, marine and solar photovoltaic (PV) energy. 

Space is the final frontier

An even more extreme approach is to put data centres in orbit where solar energy is unlimited and round-the-clock. “These giant training clusters will be better built in space, because we have solar power there, 24/7. There are no clouds and no rain, no weather,” said the CEO of a hyperscaler at a tech event in Italy last October. “We will be able to beat the cost of terrestrial data centres in space in the next couple of decades.”

A US firm claims to have successfully tested edge processing tasks in space, including data handling for a Texan AI developer, from a data centre “the size of a hardback book” as part of the payload on a US satellite launch in 2025. “This is where the future begins for this new resilient layer of critical global infrastructure,” says the firm’s CEO. “By proving that our technology can operate in space, we are one step closer to establishing the [area between Earth and Moon] and the Moon as the ultimate off-Earth storage and data resiliency solutions.”

In December 2025, another US company claimed that its satellite was the first to run a version of Google Gemini in space and the first spacecraft to train an LLM. It envisages gigawatts of compute will be deployed in space in the near future.

The European Commission has also explored the feasibility of orbiting data centres. A report published by a French and Italian aerospace group determined that deploying data centres in space “could transform the European digital landscape, offering a more eco-friendly and sovereign solution for hosting and processing data.”

The project aims to deploy one gigawatt of capacity before 2050 and suggested it would return “several billion euros” on investment between now and 2050. According to a white paper from one of the space data centre developers, the continuous illumination allows orbital solar arrays to achieve a 95% capacity of solar energy generation compared to 24% for terrestrial farms, while peak power generation in space is 40% higher due to the absence of atmospheric losses.

Nonetheless there are clear risks. Commercial exploitation of low earth orbit is a frontier science with multiple challenges including the difficulty of remote maintenance, the possibility of launch failures, and the need for a solution to cool equipment because conventional cooling systems don't work well without gravity. The cost alone could be prohibitive with every kilogramme sent into space costing at least USD 3000.

But who knows? The development of tech solutions is advancing at such a rapid pace that predictions that seemed a little mad only a few years ago are now becoming reality.

 

Comcast secures lock on UK commercial TV

Streaming Media

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ITV is to sell its media and entertainment division, including its broadcast channels and ITVX streaming service, to Sky for £1.6 billion ($2.1bn), marking one of the most consequential restructurings in modern British broadcasting. The deal positions Sky, owned by Comcast, as the UK’s largest commercial broadcaster and creates a new domestic heavyweight designed to compete more aggressively with global streaming giants such as Netflix, Amazon and YouTube.

The move has been in train for a while and already has significant synergies in advertising technology. Comcast now shares with Sky, ITV and Channel 4 its Universal Ads marketplace which enables first time, small and medium-sized enterprises to create, buy, and measure premium TV advertising campaigns across the three broadcasters' sales houses.

Officially launched at the Cannes advertising festival last month, the pact between Comcast and the UK commercial broadcasters was announced over a year ago. It represents the first international expansion by Comcast for its self-service ads platform.

Sky chief executive Dana Strong called the transaction with ITV “a defining moment for British media,” arguing that consolidation is now essential as traditional broadcasters face intensifying competition and rapid shifts in viewing behaviour. ITV’s studio arm — the production powerhouse behind Love Island, I’m a Celebrity… Get Me Out of Here! and Coronation Street — is not part of the sale and will instead be spun off as a standalone London‑listed company.

ITV will receive £1.2bn ($1.6bn) in cash on completion, plus up to £200m ($267m) in performance‑related add‑ons tied to 2027 advertising revenues. The broadcaster expects to return around £950m ($1.26) to shareholders. Sky has committed to spending £2.1bn ($2.8bn) on ITV Studios content between 2028 and 2032, safeguarding long‑running franchises and ensuring continuity for viewers. As ITV noted in the deal documents, “Viewers will continue to enjoy the shows they know and love,” including Coronation Street, This Morning, and News at Ten.

The takeover will undergo intense regulatory scrutiny. The merged ITV‑Sky advertising operation would command more than 70% of the UK TV ad market, a level of concentration likely to draw close attention from the Competition and Markets Authority and Ofcom. UK government Culture Secretary Lisa Nandy has already signalled a willingness to intervene in major media mergers, and Ofcom is expected to examine issues around Sky News’ ownership and ITV’s stake in ITN, which produces ITV News, Channel 4 News and 5 News.

ITV remains legally required to provide free‑to‑air public service broadcasting until at least 2034, meaning Sky must honour obligations around peak‑time national news, regional output and UK production quotas. Analysts warn that significant job losses are likely as duplicated functions across the two organisations are rationalised.

The deal comes amid wider upheaval at Comcast, which last week announced plans to spin off its media assets — including Sky and NBCUniversal — into a separate publicly listed company. For ITV, the sale marks a strategic pivot away from the structural pressures facing traditional broadcasters. As ITV chair Andrew Cosslett put it, the transaction “secures ITV’s crucial role as a public service broadcaster” while giving the combined business the scale to compete globally.

The takeover is expected to complete in the second half of 2027, subject to regulatory approval. For now, ITV Studios will emerge as a pure‑play production company, while Sky gains a powerful new free‑to‑air platform — a reshaping of British television that would have been unthinkable just a decade ago.

The power and challenges of AI in Africa

IEC e-tech

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How is artificial intelligence (AI) used on the African continent and what are the specific demands of African countries? We survey different countries in Africa and look at their AI needs and challenges.

Governments across the world are prioritizing AI as the basis for national competitiveness and African countries are no different. A rapidly growing number of programmes, strategies, and pilot projects are being launched across the continent. As a result, public policy is being shaped to address gaps in infrastructure and specialist skills that might limit these countries’ ability to compete globally.

There are notable differences in the levels of economic maturity, compute and internet capacity as well as institutional frameworks in each country of this vast continent, but at the same time most of them share the same concerns.

One of the main ones is a common belief that in order to be independent of technologies trained elsewhere and or owned by third parties, each state should ideally develop its own sovereign AI systems. These should be engineered to reflect linguistic diversity,  address the  requirements of informal economies as well as resource‑strained public services.

A May 2026 study by PwC found that an overwhelming majority of African organizations are already engaging with AI but also that few had succeeded in building out the technology “in ways that generate sustained growth, operational reinvention or competitive advantage.”

As AI rises up on the agenda, countries that invest in inclusive strategies, automation, innovation, and broad AI education - backed by serious funding and robust national policies - will be positioned to lead.

This article snapshots a selection of African countries and their pathways to engaging with AI.

Kenya: from maternal chatbots to helping farmers

The Kenya AI Strategy 2025–2030 aims to establish a strong digital infrastructure for AI. It outlines priority AI applications envisioning, for instance, a maternal health chatbot conversant in local dialects, AI-driven teaching systems and translating agriculture data into “farmer-friendly audio formats in local languages.” However, as the strategy document makes clear, current infrastructure limitations “could slow down AI adoption and limit the scalability of AI driven solutions across the country.”

It also acknowledges that Kenya’s current regulatory environment for AI is “fragmented”, causing “inconsistencies and inefficiencies” in AI  governance, in turn, “making it challenging to create a cohesive strategy for AI development and deployment.”

“Like many countries, the government was initially slow to act on AI governance,” says Monica Okoth, Assistant Manager in the Electrotechnical & ICT Division at the Kenya Bureau of Standards (KEBS). “Policy makers didn’t fully understand the technology, so there were no policies for a long time.” She says it was the private sector which led the government to draw up an AI strategy and that KEBS was brought into the process largely through private sector engagement.

Data ownership is a challenge

In particular, there are concerns about data ownership. Big tech companies have previously collected indigenous knowledge or language data without full disclosure, in addition to plundering the continent’s resources for their requirements. (so-called techno-colonialism). “For example, there was a case where biometric data was collected from communities without proper government knowledge or transparency. The issue isn’t the data collection itself since we need more data to reduce bias,” Okoth says, “but ensuring full disclosure, consent, and clarity on how the data will be used.

Another concern is whether AI can take into account the diversity of African populations. “Kenya has 42 languages, so developing models for all of them would require huge investment,” she adds. “Because English and Swahili are widely spoken, some therefore argue that we don’t urgently need large language models (LLMs) in every indigenous language.”

Digital safety, privacy and security were part of a more than USD 1 billion investment led by Microsoft and an Emirati AI company to build and run a data centre for East Africa in Kenya’s Rift Valley. The project promised to operate a “trusted data zone” under which local data would be stored and governed by local laws.

However, since being announced in 2024, the project has yet to kick off, with reports of development being tied up in red tape and concerns about how much electricity from the grid is needed to run it.

Role of KEBS and standards 

Recognizing the importance of international standards, KEBS joined as a participating member of ISO/IEC JTC 1/SC 42: Artificial Intelligence, in 2020. “We pushed for standards to be embedded in Kenya’s national AI strategy, because without them, implementation would be weak,” Okoth explains. “One of the government pillars now includes developing standards for conformity assessment and responsible AI.”

KEBS has already adopted several international standards and is developing local ones. For example, Kenyan Standard KS 2007:2025, a Code of Practice for AI, outlines non‑functional requirements and includes a full clause on trustworthy AI. It assigns responsibilities across the data providers, developers, software managers, and end users.

“Implementation is challenging if standards aren’t enforced or understood, so we also focus on conformity assessment. With donor support (such as funding from the UK government) we’re developing AI and AI‑data maturity models. These help organizations, especially start-ups and government agencies, self‑assess their readiness for responsible AI adoption or development. We’re also creating playbooks to guide them,” Okoth says.

Nigeria: building AI based on wide variety of languages

With over 500 languages, Nigeria is one of the most linguistically diverse countries in the world. A LLM currently in development aims to capture and build on this resource. N-ATLAS, short for Nigeria’s African Tongue Language AI System, is designed to handle multiple languages native to Nigeria, including Yoruba, Hausa, Igbo, and Nigerian-accented English.

Launched last September, the centrepiece of Nigeria’s National Artificial Intelligence Strategy (NAIS), it is a public-private initiative led by the National Information Technology Development Agency (NITDA), the National Centre for AI and Robotics (NCAIR) and local AI firm Awarri.

“N-ATLAS is designed to understand and generate Nigeria’s diverse voices, ensuring that the country’s linguistic richness is preserved and reflected in the global Artificial Intelligence (AI) ecosystem,” the Federal Ministry of Communications, Innovation & Digital Economy says.

For instance, farmers could use voice-based queries in Hausa to access weather forecasts or market advice. Igbo-speaking students might interact with AI tutors in their native tongue, improving learning outcomes in areas with low literacy rates. Or the LLM could be tuned to customer service where people’s queries “might differ significantly due to cultural and linguistic factors.”

The NAIS acknowledges existing structural challenges in the way of achieving its vision to make Nigeria a global leader in ethical and inclusive AI innovation. To upgrade its data centre and edge computing infrastructure, there are plans to offer tax breaks to investors. To build up its software capacity, organizations like Data Science Nigeria (DSN) offer upskilling and mentorship programmes. The Nigeria AI Scaling Hub is a research incubator focused on AI solutions in health, education, and agriculture, funded by the Gates Foundation. Additionally, the national curriculum for basic and secondary schools has been revamped to incorporate learning about AI, robotics, and cyber security. As DSN put it, “Africa cannot negotiate its place in an AI-driven world without the technical workforce required to hold that position.”

South Africa is leading the way

By most measures, South Africa is the continent’s leading country when it comes to digital and AI development. One report ranks South Africa as the only African country exceeding the global average of working age adults using AI tools. Another identifies more than 725 AI start-ups in the country at the end of last year, significantly more than the next best on the continent (Nigeria with 456).

Its National AI Policy Framework, released in 2024, placed “a strong emphasis on a human-centred approach in AI systems”, stipulating that applications should augment rather than replace human decision-making. And yet plans to cement this as national policy had to be put on hold earlier this year after it was revealed that some of the rules in the draft were AI-generated. At least six of the document’s 67 academic citations were found not to exist, suggesting that the draft did not in fact have sufficient human oversight.

“We need to make sure we have all the right voices at the table: people deeply immersed in AI, but also people in policy, law, and other areas,” explains Professor Benjamin Rosman, Director, Machine Intelligence & Neural Discovery, [JF1] at Wits University told CNBC Africa.

He is tasked with leading an advisory panel to the government to develop a new national AI policy. In his interview to CNBC Africa, he stressed that people working in the field were already seeking to bring in different perspectives to their work. Designing something “future-proof” should stand them in good stead, he explained.

Much of the investment in South Africa’s data centre and cloud infrastructure has come from overseas. Notably from Microsoft, which recently pledged a USD 329 million expansion in cloud infrastructure and AI training for Africa’s youngsters (a cumulative USD 1,4bn investment in recent years). Google and Amazon also all operate major platforms in Johannesburg and Cape Town.

These moves by overseas tech companies are viewed with a degree of suspicion by several south African pundits involved in the field. Rosman, for instance, queried whether South Africa should be happy relying on US technology and that subscription fees for it are leaving the country. “The country needs to build its own critical mass, widen participation, and ensure it is aligned with global best practices around AI, and plot a way forward,” he advised.

Egypt is an early adopter

The aim of Egypt’s National AI Strategy (2025-2030) is to have AI contribute as much as 7,7% of total GDP by the end of the decade. Achieving this would require training 30 000 specialists, supporting 250 startups, and expanding use of AI tools to over 35% of the total population (40 million people).

Egypt was an early mover on the continent, having issued an early AI framework for growth in 2021. The second edition is “much more ambitious” with a significant shift from solely using foreign technology to creating a sovereign AI ecosystem.

Core to that goal is development of Egypt’s first nationally built and owned LLM, called Karnak, which was announced at the AI Everything MEA summit in Cairo last February. Karnak is intended to “preserve linguistic and contextual relevance, especially for Arabic,” and to underline Egypt’s push to become “a regional AI hub linking Africa, the Levant, and the Gulf states.” 

Applications powered by Karnak include a personalized AI tutor supporting Egyptian history education in high schools, a specialized translation tool and a suite of natural language processing engines for colloquial Arabic.

Both editions of the AI strategy put ethical and responsible use of the technology at its core. As established in the Egyptian Charter for Responsible AI, the state is adapting international standards like UNESCO’s Recommendation on the Ethics of AI and ISO/IEC 42001, the International Standard for AI management systems, to local contexts, emphasizing human-centeredness, transparency, fairness, accountability, and privacy.

The work of African standards organizations 

Several initiatives have emerged recently to develop cross‑border AI standards for Africa.

EAC (East African Community) recently called for the responsible development of AI and stronger regional collaboration to drive inclusive growth and innovation. AFSEC (African Electrotechnical Standardization Commission) is creating a new technical committee on AI, including AI-enabled products and services, with specific consideration of African regional requirements, conditions, and priorities. It will be launched next month at its 10th General Assembly.

ARSO (African Regional Organization for Standardization): established a technical committee on information technology with a proposal for a subcommittee to deal with emerging technologies such as AI and IOT in May of this year.

“The goal is to create Africa‑centric AI standards,” explains Okoth. “It doesn’t make sense for each country to reinvent the wheel when resources are limited. Many African countries share similar cultural and economic contexts, so pooling resources to develop continental standards is more efficient and impactful.”

 

TNT Sports prepares to take on Commonwealth Games broadcast

Streaming Media

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TNT Sports promises an approach shaped by its Olympic experience as it prepares to produce 600 hours of coverage of the 2026 Commonwealth Games in Glasgow, July 23 to August 2.

The US-based broadcaster has landed the keys to the quadrennial multi-sport event from the BBC which declined (on grounds of cost) to cover the 23rd edition of the Games after 72 years in the role.

A total of 74 nations and territories will participate in the Games across ten sports, several with their para equivalent, competing for 165 medals. They include Australia and Canada as well as Uganda, Trinidad & Tobago and Norfolk Island, in the Pacific which has a population of just 2000.

A centrepiece of TNT Sports’ coverage is a linear channel it calls ‘360’ available on TV and HBO Max for viewers in the UK and Ireland.

“360 is a product born from TNT’s learnings as an Olympic broadcaster, particularly from Paris 2024, and from the evolution of HBO Max as a sports‑plus‑entertainment platform,” explains Scott Young, EVP, Warner Bros. Discovery Sports Europe.

“It’s the opportunity for audiences to take a lean‑back experience into watching something as complicated as a multi‑sport event like the Commonwealth Games,” he says. “We will deliver the most interesting, informative and engaging moments of the Games at that moment.”

The show will blend field‑of‑play action with athlete interviews, pre‑competition preparation, behind‑the‑scenes access and social‑first content gathered by TNT’s digital teams. Young calls it “an immersive 360 approach to how we tell the story of Glasgow 2026.”

The Commonwealth Games is an evolution of an event first held nearly a century just as the British Empire was on the verge of crumbling. It was intended to bring together athletes from across the Commonwealth of Nations, a political association comprising the majority of former territories of the British Empire.

That intent still exists, albeit that the union of countries which maintain the British King as their head of state is increasingly anachronistic.

This edition of the Games is also smaller, with just 10 sports compared to 20 when the event was held in Birmingham, UK four years ago. That’s reflective of the event’s troubled recent history. Australia’s was awarded the host for this year but decided to bow out in 2024 citing escalating costs. Glasgow stepped in as the fallback solution because it could reuse existing stadia from 2014 when it previously hosted the Games and provided it could all be managed within a £125m-150m ($199m) budget.

The sports include athletics artistic gymnastics, track cycling and weightlifting as well as Para-powerlifting, Para-bowls and 3x3 wheelchair basketball.

With the BBC having covered the Games for more than seven decades, Young is clear that TNT is not attempting to replicate that legacy style.

“We definitely haven’t modelled our coverage based on the history of the coverage,” he says. “We put forward what we thought was the right fitting coverage for Glasgow 2026, and we’re delighted Commonwealth Sport saw our approach as the way to take it forward.”

Sunset + Vine host produced the previous two Games but this time around the baton has passed to Geneva-based Actua Films which has a contract with the EBU to produce live events such as the 2024 European Athletics Championships.

TNT will take the host feed and augment it with interviews, athlete access and storytelling around the sports.

Its production model is heavily remote, drawing on infrastructure in London and Paris.

Young says TNT has nearly 230 people on site in Glasgow, with almost double that working remotely.

Signal distribution and contribution between Glasgow and TNT’s main production centre in Chiswick are handled using in‑house capabilities. Control rooms in Paris are also in use, with Timeline supporting RF delivery and multilink assisting with camera and audio components.

“We haven’t taken a view that we need a large technical supplier on site because it is a remote production,” Young explains. “It’s really cameras, microphones, return feeds, IFB, interconnectivity and comms across all the venues.”

The main studio is located at the Hydro, giving presenters proximity to multiple venues and enabling on‑air teams to interact with daily shows.

Young says the Games are “a pretty data‑rich environment,” but TNT’s Olympic experience has taught them that athlete storytelling often outweighs graphic complexity.

Host broadcast graphics will support the main sports, while TNT will use augmented reality to introduce athletes and explain sports that viewers may not traditionally follow.

Multiview and Social‑Native Production

TNT is positioning HBO Max as the central hub for immersive viewing. Multiview — already used across other sports — is being “heroed” for the Commonwealth Games.

This platform-curated feature allows viewers to watch up to four events simultaneously on one screen, with the option to switch between screens.

“You can dive into every sport and every moment on HBO Max,” Young says. “Multiview gives you the top four options of that moment. Click any box and it comes up full screen, with audio following vision.”

He encourages viewers to try it, especially those exploring unfamiliar sports.

“We’ve been an Olympic broadcaster for many editions now,” he says. “We’ve developed how our streaming platform has come along, and we’ve put the power of consuming these Games in the hands of the customer.”

He believes TNT’s combination of technical capability and editorial ambition is now a “superpower” for large‑scale events.

Young emphasises that TNT treats social content as a distinct editorial discipline rather than a derivative of linear output.

“Some broadcasters think the linear feed is the content for social media. We have a very different view,” he says.

TNT’s in‑house creators, both in London and on site, produce native vertical content, behind‑the‑scenes access and athlete‑driven storytelling. All tools are cloud‑based, allowing remote publishing.

TNT’s deal covers only the 2026 Games, but Young says future ambitions will depend on audience response. The next Games will be held in Ahmedabad, India, in 2030.

“Success is a highly engaged audience enjoying Glasgow 2026 as an event,” he says. “We want people to realise there is a new way to experience something like the Commonwealth Games.”

If viewers embrace the multi‑sport immersion, TNT will consider pursuing future editions.