The Model Y, Tesla’s best-selling compact SUV, has seen surging popularity, especially with recent price adjustments and the $7,500 federal EV tax credit still applicable in 2025 (assuming no policy changes). A sell-out across 29 states could reflect a demand spike, possibly tied to seasonal buying (e.g., Q1 closeouts) or a refreshed model rollout like the Juniper variant. Tesla’s production, primarily from Giga Texas and Giga Shanghai, might be lagging due to supply chain issues, factory retooling, or prioritization of other models (e.g., Cybertruck ramp-up). This could deplete new inventory in these states. Tesla’s inventory isn’t uniform nationwide. States like Texas (near Giga Texas) or high-EV-adoption areas like Maryland might clear stock faster due to proximity or market preferences.

Tesla often shifts focus to custom orders when pre-built inventory runs low. A “sold out” claim might mean showroom/demo stock is gone, but buyers can still order for later delivery. If true, immediate buyers in these states might face delays or turn to used Model Ys, potentially driving up secondary market prices. Posts on X hint at excitement over this scarcity, suggesting Tesla’s brand strength. Depleted inventory could signal Tesla pushing production limits or intentionally tightening supply to maintain pricing power—common in their playbook. A multi-state sell-out underscores EVs’ growing foothold, especially in conservative states like Alabama or Mississippi, alongside EV-friendly ones like Maryland.

Tesla has faced a variety of production challenges in 2025 that could contribute to the reported sell-out of new Model Y inventory across multiple U.S. states. While a complete sell-out suggests strong demand, it could also reflect supply-side bottlenecks limiting available stock. Tesla has encountered difficulties securing domestically sourced components for its electric vehicles (EVs) and lithium-ion batteries. Global supply chain issues, including shortages of semiconductors and raw materials like lithium and nickel, have persisted into 2025. These constraints could reduce production output at key facilities like Giga Texas and Giga Shanghai, potentially explaining low inventory levels in states like Texas, Michigan, and others.

For instance, battery supply issues have been flagged as a significant hurdle, with X users suggesting that Tesla’s battery factory is struggling to meet demand. This aligns with Elon Musk’s past comments about the complexity of battery production, which involves dozens of cell variants Tesla aims to streamline. Reports that Giga Austin is “not running well,” with potential halts in Cybertruck deliveries. While Tesla’s Q4 2024 production numbers (459,000 vehicles) were robust, any slowdown in Texas—where Model Y is a primary output—could tighten supply in nearby states like Oklahoma, Arkansas, and Missouri.

European production has faced challenges, with demand in Europe reportedly so low that Giga Berlin operates at a fraction of its 1-million-vehicle annual capacity (around 250,000 units). However, a transition to a new Model Y variant has also slowed output, as confirmed by Tesla GigaBerlin’s Factory Director. This could indirectly affect U.S. inventory if resources are reallocated. As a major exporter to the U.S., any production hiccups in China—due to competition from BYD or geopolitical tensions—might limit Model Y shipments, impacting states like Hawaii or Maryland.

Tesla is reportedly shifting production lines to accommodate a refreshed Model Y (possibly the Juniper variant) and preparing for a lower-cost vehicle slated for mid-2025. Retooling factories, as seen with the Model Y transition in Berlin, often reduces output temporarily. This could explain why new inventory is depleted across 29 states, as Tesla prioritizes future models over current stock replenishment. Historically, Tesla has struggled to scale production efficiently. Elon Musk has called scaling “1,000% to 10,000% harder than making prototypes,” a sentiment echoed in past Reuters reports. In 2025, ramping up Cybertruck production and preparing for a new affordable EV (expected H2 2025) have stretched resources.

Tesla’s 2024 delivery numbers (1.79 million vehicles) marked its first annual decline, with Q1 2025 forecasts at 367,000—down from 386,810 in Q1 2024. While the sell-out might indicate high demand, analysts argue Tesla faces a “demand problem,” with unsold inventory (47,000 units in Q4 2024) piling up earlier this year. Production challenges could exacerbate this by failing to meet even softened demand, depleting stock in states like Georgia, Virginia, and Utah. Posts on X and articles from sources like MotorTrend highlight internal chaos, with claims of “messy” manufacturing, unmet quotas, and reps “making up lies to buy time.”

Musk’s focus on side ventures (e.g., Department of Government Efficiency) has drawn criticism from investors like Christopher Tsai, suggesting distracted leadership might hinder production fixes. Tesla’s aging lineup—Model Y launched in 2020—faces stiff competition from cheaper Chinese EVs like BYD’s offerings, potentially forcing price cuts that squeeze margins and limit funds for production expansion. Supply chain woes, factory inefficiencies, and retooling have capped the number of Model Ys produced, leading to rapid depletion of pre-built stock. Tesla might prioritize high-demand markets (e.g., California, unlisted here) or custom orders over stocking showrooms in less dense states like Wyoming or Montana.

Looking Ahead

Tesla’s production challenges in 2025 could ease if Giga Texas stabilizes, the Model Y refresh completes, and supply chains recover. Musk’s promise of 20-30% delivery growth in 2025 hinges on starting production of a cheaper EV in Texas by mid-year, but skepticism remains due to these persistent hurdles. For now, the sell-out might reflect both Tesla’s popularity and its struggle to keep pace—a bittersweet testament to its market position.

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.

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.