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MultiChoice Price Hike: NGO Accuses Pay-TV Giant of Discriminatory Pricing Against Nigerians

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A consumer rights advocacy group, Save the Consumers, has launched a scathing attack on MultiChoice Nigeria over its recent 21 percent price increase on DStv and GOtv subscriptions, which took effect on March 1, 2025.

The group described the hike as exploitative, discriminatory, and a blatant disregard for Nigerian consumers, particularly in light of the company’s decision to slash prices by up to 38 percent for its South African subscribers.

This latest backlash against MultiChoice adds credence to a growing perception that Nigerians are quick to protest against multinational corporations, particularly when it comes to pricing and service delivery. While local businesses and essential goods suppliers have significantly increased costs amid rising inflation and economic hardship, few consumer advocacy groups have taken up the fight against these domestic price surges with the same intensity.

The development has also put regulatory authorities and legal bodies on high alert, with MultiChoice now facing regulatory scrutiny and legal action over its tariff hike. The Federal Competition and Consumer Protection Commission (FCCPC), which had earlier directed MultiChoice to halt all price increases pending an ongoing investigation, is under pressure to act decisively.

In a statement condemning MultiChoice’s action, Executive Director of Save the Consumers, Dr. Aliyu Ilias, accused the company of ignoring regulatory directives and treating Nigerian subscribers unfairly compared to their South African counterparts.

“Coming less than a year after the May 2024 price hike in Nigeria, this new increase openly defies a directive from the FCCPC to suspend all price adjustments pending the conclusion of ongoing investigations. It reflects MultiChoice’s clear disregard for both Nigerian consumers and regulatory authority,” he said.

Dr. Ilias argued that MultiChoice’s justification for the price hike—economic difficulties in Nigeria—was inconsistent, given that the company lowered fees in South Africa and even introduced additional content and features to enhance consumer experience.

“In South Africa, MultiChoice has lowered fees on various products, added new channels, and introduced features that improve the user experience, all while acknowledging the financial pressures faced by South African households. Yet, in Nigeria, the same company claims that economic difficulties justify higher tariffs,” he added.

The South Africa-Nigeria Comparison: A Dismissed Argument?

Some observers have pushed back against the NGO’s comparison of MultiChoice’s pricing strategies in Nigeria and South Africa. Many have noted that the economic environments of both countries are vastly different, making direct price comparisons misleading.

South Africa’s economy, while facing challenges, operates within a more stable macroeconomic framework compared to Nigeria, which has been grappling with currency devaluation, inflation, and worsening economic headwinds.

South Africa has a much more stable exchange rate, lower inflation, and different regulatory frameworks, leading many to conclude that it is unrealistic to expect MultiChoice to apply the same pricing model in both markets.

Even within Nigeria, businesses across all sectors have been forced to increase prices due to escalating costs. From food prices to transportation, utilities, and household essentials, almost every service and product has seen sharp price surges.

Why Are Nigerians Protesting MultiChoice but Not Food Prices?

This raises a critical question: Why are Nigerians protesting against MultiChoice but not mobilizing against the increase in the cost of goods and services, particularly food?

Over the past year, food prices have skyrocketed, with staple items like rice, bread, and tomatoes more than tripling in cost. The cost of transportation, healthcare, and education has similarly risen, yet there have been no large-scale protests against these issues.

A common explanation is that MultiChoice operates in an industry where consumers have historically felt exploited, due to its dominance in the pay-TV market. Many Nigerians perceive the company as taking advantage of limited competition to set prices arbitrarily, unlike the food industry, where price fluctuations are often attributed to external economic factors beyond retailers’ control.

MultiChoice’s Defense

MultiChoice has defended its decision, citing rising operational costs, currency fluctuations, and inflationary pressures in Nigeria. The company maintains that it is not alone in increasing prices, as nearly every business operating in Nigeria has been forced to adjust pricing to stay afloat.

The company also pointed out that despite the price hike, Nigerians still have access to a variety of packages at different price points, ensuring affordability for a broad consumer base.

However, Save the Consumers insists that the increase is unjustifiable and has called for regulatory intervention to prevent future price hikes. The NGO has urged the FCCPC and the National Broadcasting Commission (NBC) to:

  • Investigate MultiChoice’s pricing model and determine whether its tariff structure is anti-competitive.
  • Enforce consumer protection laws to prevent monopolistic practices.
  • Introduce new policies to encourage competition in the pay-TV sector and break MultiChoice’s dominance.

Additionally, consumer advocacy groups are urging Nigerians to explore alternative streaming platforms as a means of protesting what they describe as MultiChoice’s exploitative pricing policies.

The Limits of Scaling: AI Researchers Grow Skeptical About AGI As Predictions Fail to Materialize

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For years, tech leaders have assured the world that artificial general intelligence (AGI)—AI that matches or surpasses human cognition—was just around the corner. But despite unprecedented investments and a relentless push to scale AI models, AGI remains elusive.

A new survey of 475 AI researchers, conducted by the Association for the Advancement of Artificial Intelligence (AAAI), reveals a growing consensus: simply throwing more computing power at AI is unlikely to lead to AGI.

The findings challenge a widely held assumption among major AI players, who have spent the last decade racing to build larger and more complex AI models in the hope that one would eventually “crack” intelligence. However, 76% of surveyed researchers now believe that scaling up existing models is “unlikely” or “very unlikely” to lead to AGI.

This growing skepticism comes as the self-imposed timeline for AGI by industry leaders is beginning to elapse—with little to show for it.

Industry Predictions Are Falling Apart

In 2014, Elon Musk famously claimed that AI could surpass human intelligence within a decade. By 2017, he doubled down, warning that humanity was “summoning the demon” and that superintelligent AI could arrive by 2025. His aggressive predictions have been echoed by other tech figures, including OpenAI’s CEO Sam Altman, who has frequently suggested that AGI could emerge in the near future.

Yet, despite billions in investment and the development of AI models with trillions of parameters, AGI has yet to materialize. Instead, the most advanced AI models, like OpenAI’s GPT-4, Google’s Gemini, and Anthropic’s Claude, are still limited to pattern recognition and language prediction. They remain far from demonstrating genuine reasoning, problem-solving, or self-awareness—the hallmarks of true AGI.

Even Demis Hassabis, CEO of Google DeepMind, has struck a more cautious tone. In contrast to Musk’s warnings, Hassabis estimates that AGI might emerge within the next five to ten years—a far more reserved prediction than those made by some of his peers. But even this timeline remains speculative, as researchers increasingly argue that fundamental breakthroughs will be needed before AGI becomes a reality.

Why More Computing Power Isn’t Enough

The last few years have seen unprecedented investment in AI research. In 2023, venture capital funding for generative AI exceeded $56 billion, according to TechCrunch, and demand for AI accelerators contributed to the semiconductor industry hitting a record $626 billion in 2024. Companies like Microsoft, Google, and Amazon have gone as far as securing nuclear power deals just to meet the energy demands of training and running these massive AI models.

Yet, despite these investments, AI progress appears to be hitting a wall. OpenAI’s latest models, while introducing new capabilities, have shown only marginal improvements over their predecessors. AI researcher Stuart Russell of UC Berkeley described the situation to New Scientist.

“The vast investments in scaling, unaccompanied by any comparable efforts to understand what was going on, always seemed to me to be misplaced,” he said.

This problem has become more apparent as models hit performance plateaus. In the past, expanding model sizes from 10 billion to 100 billion parameters yielded substantial improvements. But more recent expansions—from 100 billion to 1 trillion parameters—have produced diminishing returns. This has led many in the AI research community to question whether scaling alone will ever be enough to reach AGI.

A Shift in AI Research Priorities

As skepticism grows, AI researchers are rethinking their priorities. Many are now shifting their focus from simply building larger AI systems to ensuring these systems operate within an acceptable risk-benefit profile. While AGI remains an area of interest, only a small fraction of researchers are actively pursuing its development.

There is also growing support for the idea that if AGI is developed by private companies, it should be publicly owned to mitigate risks. Despite concerns about safety, a majority of researchers believe that AGI research should continue, rather than be halted until full safety mechanisms are in place.

Some researchers are exploring alternative approaches to scaling, such as “test-time compute.” Instead of blindly increasing model size, this method allows AI to spend more time “thinking” before generating responses, leading to performance improvements without a massive surge in computing power. OpenAI has experimented with this approach, but Arvind Narayanan, a computer scientist at Princeton University, warns that it is “unlikely to be a silver bullet.”

Tech CEOs Still Cling to the Scaling Dream

Some industry leaders refuse to abandon the belief that scaling alone will lead to AGI. Google CEO Sundar Pichai recently stated that the industry can “just keep scaling up”, though he acknowledged that the era of easy AI breakthroughs is coming to an end.

This divide between corporate optimism and academic skepticism raises the question: is AGI truly within reach, or has the industry been chasing a mirage?

Presently, AI is advancing, but not in the way that was promised. The lofty predictions of AGI arriving by 2025 are looking increasingly unlikely, and even the more cautious estimates—such as Hassabis’ 5-10-year timeline—remain speculative. Against this backdrop, the belief that AGI is not for the near future is gaining traction.

As scaling shows diminishing returns and researchers shift toward more cautious, risk-aware development, the AI industry may soon be forced to rethink its entire approach. If AGI is to be achieved, it will likely require new paradigms—not just bigger models and more data.

NigComSat Calls Innovators To Build Nigeria’s Satellite Future

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My position is that 25% of the Nigerian military non-personnel budget should be spent on Nigerian companies and startups, on systems development, and production. If we implemented that policy when I pushed it in 2017, Nigeria today would be a net exporter of military-grade gadgets because many defense-related startups would have mushroomed. Sure, defence gadgets, not offence.

So, reading that a Nigerian agency is examining a construct where those with ideas could be supported, I want to share in case there are young people with great ideas. NigComSat, the government satellite agency, is looking for entrepreneurs and startups  in the broad domain of satellite and digital communication.

The NIGCOMSAT Accelerator Programme 2025 is now open for applications! Gain access to mentorship, funding opportunities and cutting-edge satellite technology to scale your innovation.

Application Deadline: April 11, 2025

Who Can Apply? Nigerian startups in tech, space, and digital solutions

Apply Now: https://lnkd.in/dmDzEPkP

After you have gone through the NIGERIAN COMMUNICATIONS SATELLITE LIMITED (NIGCOMSAT) program, and you are able to demonstrate a possibility to use infra-red or related tech to track movements of people in the bush in near real time, Tekedia Capital will like to explore investment in your company. And through FASMICRO partnership with Intel Corp (the only in Africa), my electronics business will provide you with cutting edge programmable processors to scale (see on Intel website ). Together, we can secure cities and build a security fortress across Nigerian communities.

Jane Egerton-Idehen, CEO of NigComSat, I hope you discover great startups, and if you do, we will provide support.

Crypto-Fuelled Game Shows: The Next Gen Way to Play Classic Game Shows?

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Crypto is transforming many industries. But, when will it be integrated into game shows? And, how is the game show landscape already evolving? Let’s take a look.

New Ways to Play Classic Game Shows

Classic game shows are already evolving, due to technological developments and adapting to consumer interests. Take the show Deal or No Deal, for example. The format of this show has been around since the year 2000, introduced by the German show Die Chance deines Lebens and Dutch show Miljoenenjacht. The game show then came to US and UK TVs in 2005.

In the UK, Deal or No Deal became incredibly popular in both its 2005-2013 and its revival from 2023. But, playing the game show itself is not the only way it can be enjoyed in the UK. The show has even been transformed into online casino games like Deal or No Deal Lightning Spins. The game uses recognizable icons from the show like the banker’s wax stamp, telephone, and red boxes for an authentic virtual experience. These games are accessed through online platforms for immersive and engaging virtual experiences.

Elsewhere, Deal or No Deal is also seeing a revival in the US thanks to a reboot that transformed the way that the game can be played. Launched in 2024, this show has just aired its second season, combining elements of the classic game show with elements of reality TV shows like Survivor. In Deal or No Deal Island survivor compete in physical challenges to find briefcases with associated cash values. The contestants then play a Bankers Challenge (aka your classic Deal or No Deal). This reality show twist, along with using technology to create immersive virtual games, has allowed Deal or No Deal to adapt to consumer demands and remain relevant in the modern entertainment landscape.

Cryto X Game Shows

As the ways to play classic game shows are already evolving, it is only logical that people have begun to question how and when crypto might be incorporated into these game shows. In one sense, crypto is already making waves in the industry with the creation of crypto-fuelled versions of competitions from shows like Squid Game and Survivor.

Just last year, for example, there was a Survivor-style competition that incorporated elements of real-world scavenger hunts, online gameplay, and strategy. Players use 0.1 ETH to join a tribe, and had to scour Brooklyn for secret codes and compete in online games to kick people off their crypto island. The aim of this was to show that people don’t have to watch competition shows – they can participate in it through the internet with the help of crypto.

Of course, another way that crypto might be utilized in games shows is in the transfer of the winning jackpot. One of the key benefits of crypto is cheaper and faster money transfers, which can often be made 24/7. This could improve the efficiency of winning contestants getting their prize. The tokenized winnings could also gain value depending on market conditions, which could significantly affect the end prize pot.

That said, there are still some negatives to crypto that keep it from being a mainstream wallet essential. However, we’ll just have to wait and see how crypto might affect the game show landscape.

Rivalry in the AI/Chip War is Fueled by a Mixed-up Factors

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The AI/chip war is a fast-moving, ever-shifting battlefield. It’s driven by rapid advancements in semiconductor tech, fierce competition between companies like Nvidia, AMD, Intel, and TSMC, and the growing demands of AI workloads. Countries are also in on the game, with the U.S., China, and others jockeying for supremacy in both manufacturing and innovation. Supply chain issues, export controls, and breakthroughs like quantum computing or new chip architectures keep it unpredictable.

The rivalry in the AI/chip war is fueled by a mix of technological, economic, and geopolitical forces. AI demands insane computational power—think training large language models or running real-time inference. Companies like Nvidia (with its GPUs), AMD, and Intel are battling to build the fastest, most efficient chips. Innovations like smaller nanometer processes (e.g., 3nm from TSMC) or specialized AI accelerators (like Google’s TPUs) keep pushing the stakes higher. Chips are the backbone of everything—phones, cars, data centers, defense systems.

Controlling the supply or leading the market means billions (or trillions) in revenue. Nvidia’s skyrocketing valuation shows how much is up for grabs. Startups and legacy players alike are pouring cash into R&D to avoid being left behind. Nations see chips as a strategic asset. The U.S. restricts exports to China (e.g., cutting-edge chips and manufacturing gear) to slow their progress, while China’s pumping billions into homegrown firms like SMIC to break free from reliance on the West. Taiwan’s role as a chip-making hub (via TSMC) adds tension, given its shaky status with China.

Shortages from the pandemic exposed how fragile the system is—everyone’s fighting to secure fabs, rare materials (like neon gas or silicon wafers), and talent. It’s a scramble to not get choked out. The next big leap—whether it’s chiplet designs, quantum chips, or something else—could flip the table. No one wants to be the one eating dust when that happens. It’s a high-stakes slugfest where the winners get tech supremacy, cash, and influence, and the losers risk irrelevance.

The push for smaller process nodes continues—3nm is mainstream with TSMC and Samsung, while 2nm is on the horizon for 2025-2026. These shrinks boost performance and efficiency, critical for AI’s power-hungry workloads. Intel’s catching up with its 18A process (1.8nm equivalent), aiming to reclaim foundry leadership. General-purpose CPUs and GPUs are giving way to specialized silicon—think Nvidia’s H100, AMD’s Instinct MI300, and a flood of AI accelerators from startups like Cerebras and Graphcore. These chips prioritize parallel processing and energy efficiency for training and running massive models.

Instead of monolithic dies, companies are stacking smaller, specialized chiplets (e.g., AMD’s Ryzen, Intel’s Meteor Lake). This cuts costs, boosts yields, and lets firms mix-and-match for specific needs—like pairing AI cores with high-bandwidth memory. After years of shortages, there’s a rush to diversify. The U.S. CHIPS Act and EU Chips Act are funneling billions into domestic fabs—Intel’s Ohio plant and TSMC’s Arizona site are ramping up. Meanwhile, firms are stockpiling critical materials and rethinking reliance on Taiwan. Export controls are tightening—U.S. restrictions on advanced lithography (like ASML’s EUV machines) are squeezing China’s ability to make cutting-edge chips.

China’s countering with heavy investment in legacy nodes (28nm and above) and alternative tech like RISC-V architectures. AI’s energy demands are insane—data centers are gobbling up electricity. Chips are trending toward low-power designs, with innovations like gate-all-around transistors and backside power delivery (e.g., Intel’s PowerVia) to keep heat and costs down. High-bandwidth memory (HBM3, soon HBM4) and on-chip memory solutions are exploding to keep up with AI’s data needs. Companies like SK Hynix and Micron are in a fierce race to supply these.

It’s early, but quantum computing’s looming—IBM and Google are making noise, and hybrid classical-quantum chips could disrupt the game. Neuromorphic chips (mimicking brain-like processing) are also bubbling up for edge AI. Big players are swallowing smaller ones (e.g., Qualcomm eyeing acquisitions), while new entrants—especially in China and India—are shaking things up. TSMC’s still king, but its dominance is under pressure. The industry’s sprinting toward a future where AI, efficiency, and self-reliance dictate who wins. What trend do you see as the biggest game-changer?