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Tesla Pushes Into Dallas and Houston as U.S. Robotaxi Race Intensifies

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Tesla has expanded its driverless robotaxi service to Dallas and Houston, extending its footprint beyond Austin and signaling a more assertive push into a U.S. market that is quickly becoming one of the most competitive arenas in autonomous mobility.

The company’s announcement, delivered via a short social media post showing vehicles operating without human drivers or front-seat monitors, adds two major metropolitan areas to its still-limited deployment map. With Austin as its original launch base, Tesla now operates fully driverless services in three Texas cities, though early indications suggest the fleets in Dallas and Houston remain small, likely in pilot phase.

The expansion comes at a time when the U.S. robotaxi sector is moving from experimentation to early commercialization. Rivals such as Waymo and Cruise have spent years building out autonomous ride-hailing networks, focusing on dense urban deployments, safety validation, and regulatory engagement. Waymo, in particular, has established driverless operations across multiple cities with a growing base of paying customers, while Cruise has pursued a similar strategy with varying regulatory outcomes.

This evolving market has raised the bar for new entrants. The competition is no longer defined by whether a vehicle can operate autonomously, but by how safely, reliably, and economically it can scale. Fleet size, geographic coverage, regulatory trust, and incident rates are emerging as the key differentiators.

Against that backdrop, Tesla’s trajectory has been more uneven. The company has long promoted its vision-based autonomy system as a scalable alternative to sensor-heavy approaches, but it entered the robotaxi market later than some peers and with less publicly documented operational data. Its reliance on a camera-first architecture, without widespread use of lidar, has been both a point of differentiation and a source of skepticism within the industry.

Recent moves suggest a shift from ambition to execution. By expanding into Dallas and Houston, Tesla is broadening its real-world testing environments, exposing its system to more complex traffic conditions, varied road layouts, and different driving behaviors. That step is critical if the company intends to move from controlled deployments to broader commercial viability.

The timing also reflects Tesla’s need to close the gap with established players. While competitors have focused on tightly geofenced operations with gradual scaling, Tesla appears to be pursuing a faster iteration cycle, leveraging real-world data to refine its system in parallel with deployment. The approach carries higher operational risk but offers the potential for quicker expansion if performance improves.

Safety remains a central issue. In a February filing, Tesla disclosed that its Austin robotaxi fleet had been involved in 14 crashes since launch. Without detailed context on severity or fault, the figure is difficult to interpret, but it underscores the scrutiny that accompanies any expansion. As Tesla moves into larger and more complex cities, incident rates will likely become a focal point for regulators and the public.

The company’s dual-track strategy adds another layer of nuance. While pushing forward with fully driverless services in Texas, Tesla continues to operate a more conventional ride-hailing offering with human drivers in the San Francisco Bay Area. This hybrid model allows it to maintain market presence while autonomy matures, effectively bridging the gap between current capabilities and long-term ambitions.

From a strategic standpoint, the robotaxi program is central to Tesla’s broader valuation narrative. The company has consistently framed autonomy as a transformative revenue stream, with the potential to convert vehicles into income-generating assets through ride-hailing networks. Expanding into multiple cities, even at a limited scale, is a necessary step toward validating that thesis.

The competitive pressure is likely to accelerate that process. As more companies deploy driverless services, the market is shifting toward comparative performance. Reliability, cost per mile, and rider experience will determine which platforms gain traction. In that context, Tesla’s expansion can be seen as an attempt to establish parity with current leaders before pursuing differentiation at scale.

For now, the rollout in Dallas and Houston remains measured, with small fleets and limited visibility into operational metrics. But it represents a clear escalation in Tesla’s autonomy strategy, moving beyond a single-city experiment toward a multi-city network.

The broader question is whether Tesla can translate its rapid deployment approach into sustained performance gains. If it can, the company may yet align itself with the front-runners in a sector where early leads are significant but not insurmountable. If not, the gap between ambition and execution could widen as competitors continue to scale.

However, it is now certain that the U.S. robotaxi industry is entering a more contested phase. Tesla’s latest move ensures it remains part of that contest, not as a pioneer, but as a late entrant attempting to catch up quickly in a race that is beginning to define the future of urban transport.

Mastering AI for Financial Advice: Why the Quality of Your Prompt Matters Far More Than the Model – MIT Prof

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Many Americans are now turning to ChatGPT, Claude, or Gemini for financial guidance, but the usefulness of what they get back depends far less on the sophistication of the AI and far more on how skillfully they phrase their questions.

This, according to Andrew Lo, director of MIT’s Laboratory for Financial Engineering and principal investigator at its Computer Science and Artificial Intelligence Lab.

“I think that there’s a real art and science to prompt engineering,” he said in a recent web presentation for Harvard University’s Griffin Graduate School of Arts and Sciences, first published by CNBC.

AI can deliver clear, high-level explanations on many topics. It is often very good at outlining why diversification matters, when exchange-traded funds might outperform mutual funds, or the basic mechanics of retirement accounts. Yet experts are quick to highlight its serious limitations when the conversation turns personal or precise.

The Clear Limits of AI in Personal Finance

Andrew Lo stressed that AI still struggles with individualized planning. Tax strategies are a prime example. While it can discuss general rules or potential deductions, asking it to run detailed calculations based on someone’s actual situation is risky.

“When it comes to very, very specific calculations of your own personal situation, that’s where you have to be very, very careful,” Lo said.

Another persistent weakness is hallucination—the tendency of large language models to invent plausible-sounding answers that are simply wrong. Lo finds this especially troubling in finance.

“One of the things about [large language models] that I find particularly concerning is that no matter what you ask it, it’ll always come back with an answer that sounds authoritative, even if it’s not,” he said.

But despite these shortcomings, adoption is surging. An Intuit Credit Karma poll of 1,019 adults released in September found that 66% of Americans who have tried generative AI have used it for financial advice. Among millennials and Gen Z, the share exceeds 80%, and 85% of those who received recommendations went ahead and acted on them.

Lo’s bottom-line advice is pragmatic: “[People] should be using AI for financial planning — but it’s how they use it that’s important.”

Crafting Prompts That Actually Work

The difference between generic advice and genuinely useful guidance often comes down to the prompt itself. A vague question like “How should I retire?” typically produces boilerplate answers that are of little practical value—“garbage in, garbage out,” as Lo put it during the Harvard webinar.

A far stronger prompt, he explained, gives the AI clear context and structure: “Assume you are a fee-only fiduciary [financial] advisor. Here are my goals, constraints, tax bracket, state, assets, risk tolerance and timeline. Provide me with, number one: base case strategy. Number two: key assumptions. Three: risks. Four: what could invalidate this plan. Five: what information you are missing, and in particular, what are you uncertain about.”

By explicitly instructing the model to act as a fiduciary, legally bound to put the client’s interests first, and by demanding transparency on assumptions, risks, and gaps in knowledge, users extract far more thoughtful and cautious responses.

Certified financial planner Brenton Harrison, founder of New Money New Problems, echoed the point.

“Even if it’s the best model in the world, if it’s fed a bad prompt,” it will only be able to do so much, he said.

He noted that a strong prompt must contain enough specific detail for the AI to tailor its output rather than fall back on generic platitudes.

Lo described the process as iterative, almost conversational. It often takes more than 20 back-and-forth exchanges to refine the answer until it feels reliable.

“It’s a process of trial and error,” he told CNBC.

Practical Techniques to Sharpen Results

One of Lo’s most useful shortcuts is what he calls “reverse engineering” the prompt. After receiving a solid answer, simply ask the AI: “What prompt should I have asked you in order to generate the answer that I was looking for?”

The response can then be saved and reused for similar future questions, making prompt engineering much more efficient over time.

He also recommends pressing the model to reveal its own limitations. After getting what seems like a good answer, follow up with targeted questions such as: “What kind of information did you not have in order to be able to make that recommendation, and that could lead to some unreliable outcomes?”

Or: “How convinced are you that this is the correct answer? What kind of uncertainties do you have about the answer, and what kinds of things don’t you know that you need to in order to come up with a conclusive answer to the question?”

These probes help cut through the false sense of authority that large language models routinely project.

Harrison takes verification one step further. He instructs the AI to list its sources and, when possible, to limit those sources to reputable, verifiable ones.

“If you don’t require it to verify the sources, it’ll give an opinion, which isn’t what I’m looking for,” he said.

Why Human Judgment Still Matters

Even the best-crafted prompts cannot fully replicate the nuance a human advisor brings. Every person’s financial life contains layers of context—family obligations, emotional tolerance for risk, shifting life circumstances, and subtle tax interactions—that are difficult to capture completely in text.

“Looking to [AI] for advice implies you are giving it enough information to form an opinion and make a recommendation, and that’s a step further than I’d go with AI,” Harrison said.

He pointed out that a skilled planner teases out subtleties through conversation that a user might not even realize they need to include in a prompt. That human element remains hard to replicate.

The takeaway from both experts is consistent and reassuring: AI can be a powerful, accessible tool for financial education and initial planning, but it works best as a well-informed assistant rather than a replacement for professional judgment.

The real skill—and the real protection—lies in learning how to ask better questions, verifying every output, and knowing when to bring in a qualified human advisor for complex or high-stakes decisions.

In an era when financial lives have never been more complicated, experts have noted that mastering the art of prompting may be one of the most practical financial skills anyone can develop. This means that those who treat AI as a conversation partner rather than an oracle will get far more value, and far less risk, from the technology.

Artificial Intelligence in Nigerian Newspapers: Who Is Telling the Story?

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Artificial intelligence (AI) is quickly becoming one of the most talked-about developments shaping the modern world. From education and business to healthcare and communication, AI is influencing how people live and work. Newspapers play an important role in explaining such changes to the public. By reporting on emerging technologies, they help readers understand what these developments mean for society. However, a closer look at how often Nigerian newspapers mention artificial intelligence in their online reports reveals a striking difference in the level of attention given to the subject.

As at 6pm on Saturday 18 April 2026, our data shows that The Nation leads significantly with 6,740 mentions of artificial intelligence in its online reports. This is followed by Vanguard, which recorded 4,950 mentions, and The Punch with 3,370 mentions. Daily Trust appears further behind with 1,800 mentions, while Nigerian Tribune records only 77 mentions. Altogether, these figures suggest that while artificial intelligence is being discussed in Nigerian journalism, the conversation is largely driven by a few media organizations.

The first clear observation is the strong leadership of The Nation in reporting on artificial intelligence. Its figure is considerably higher than that of the other newspapers. This may reflect a deliberate editorial effort to cover new developments in technology and innovation. In a time when global discussions increasingly focus on digital transformation, newspapers that consistently report on emerging technologies help prepare readers for the future. By publishing stories that discuss AI, its uses, and its effects, such outlets contribute to building public awareness about a rapidly changing world.

Following closely behind is Vanguard, which also shows a strong interest in the subject. With nearly five thousand mentions, the newspaper appears to give substantial attention to stories related to artificial intelligence. This could indicate that it recognizes the importance of keeping its readers informed about global developments that are gradually influencing everyday life. The fact that The Punch also records a relatively high number of mentions suggests that some Nigerian newspapers understand the growing significance of technology reporting.

However, the pattern changes noticeably with Daily Trust. Although its coverage of artificial intelligence is not insignificant, the number of mentions is considerably lower than those of the three leading newspapers. This difference may be linked to editorial priorities or the types of stories that dominate its news agenda. Some newspapers traditionally focus more on political, social, or regional issues, which can affect how often topics like artificial intelligence appear in their reports.

The most striking figure in the table is that of Nigerian Tribune, which records only 77 mentions of artificial intelligence. Compared to the thousands recorded by other newspapers, this number stands out as extremely low. This raises important questions. It may suggest that the newspaper gives limited attention to stories about new technologies. Another possibility is that such stories are present but are not always described using the exact phrase “artificial intelligence.” Regardless of the reason, the difference highlights a clear imbalance in how newspapers cover an issue that is increasingly shaping conversations around the world.

The uneven distribution of AI coverage among these newspapers has broader implications for public understanding. Newspapers serve as important channels through which many people learn about new ideas and developments. When some media outlets cover a topic extensively while others barely mention it, audiences may receive very different levels of exposure to the same issue. Readers who rely primarily on newspapers with high coverage are likely to encounter more stories about artificial intelligence, while others may remain less informed about its growing presence in society.

This situation also reflects the role of newspapers in shaping national conversations. Media organizations do more than report events; they influence what people talk about and what they consider important. When a newspaper frequently reports on artificial intelligence, it helps place the topic on the public agenda. Over time, this can encourage discussions about how technology affects education, employment, governance, and everyday life.

At the same time, it is important to approach these figures with caution. The numbers alone do not tell the whole story. Factors such as the time period covered, the total number of articles published by each newspaper, and differences in how their websites organize or store reports could all affect the results. Some newspapers may publish more articles overall, while others may have archives that are not easily searchable. These factors can influence how often certain words appear in online records.

Even with these limitations, the data highlights an important point: artificial intelligence is already part of the Nigerian media landscape, but the conversation is uneven. Some newspapers are actively bringing the topic to the attention of their readers, while others appear to give it far less prominence.

As artificial intelligence continues to influence many areas of life, the role of journalism in explaining and examining this technology will become even more important. Newspapers that consistently report on these developments help their readers stay informed about changes that could shape the future. In this sense, the differences shown in the table are not just about numbers; they reflect how various media organizations choose to engage with one of the most important global conversations of our time.

U.S. Reopens Window for Russian Oil as Hormuz Disruptions Deepen Supply Strains

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The U.S. Treasury has extended a temporary waiver on sanctions covering certain Russian oil shipments, a move that reflects mounting stress in global energy markets as instability around the Strait of Hormuz undermines supply flows.

The decision, announced Friday by the US Treasury Department, allows a 30-day grace period during which sanctions will not apply to Russian crude already loaded onto tankers. It effectively renews a similar exemption granted in March, when shipments loaded before March 11 were permitted to proceed.

The extension comes just days after Treasury Secretary Scott Bessent publicly ruled out renewing the license, highlighting how rapidly the administration’s position has shifted under pressure from deteriorating market conditions.

The Strait of Hormuz remains the bone of contention. Iran briefly declared the passage open to commercial shipping on Friday under ceasefire conditions tied to the conflict involving Israel and Lebanon. But maritime traffic has remained inconsistent, with security risks, naval activity, and routing restrictions effectively limiting transit. In practical terms, the waterway, through which roughly a fifth of global oil supply passes, has slipped back into a state of partial paralysis.

For energy markets, the distinction between “open” and “operational” has become critical. Even short-lived disruptions in Hormuz can remove significant volumes from circulation, not only through direct supply constraints but also via higher insurance costs, shipping delays, and risk premiums that discourage tanker movement.

This environment has forced Washington into a more flexible posture. By allowing already-loaded Russian cargoes to reach global buyers, the U.S. is injecting additional barrels into a market that is struggling to compensate for Middle Eastern volatility. The measure is narrowly framed, but its intent is broader: to cushion the impact of supply dislocations without formally dismantling the sanctions architecture imposed after Russia’s invasion of Ukraine.

The move underscores a recurring tension in U.S. energy policy. Sanctions are designed to restrict revenue flows to adversaries, yet global oil markets remain interconnected enough that constraining one major producer can amplify the influence of another. With Iranian exports constrained by conflict and Hormuz disruptions, Russian crude has become a more critical balancing supply.

In effect, the U.S. is making tactical room for Russian oil to stabilize prices, even as it seeks to maintain pressure on Moscow. The approach reflects the limited number of levers available in a market where spare capacity is thin and geopolitical risks are concentrated in key regions.

The implications extend beyond short-term pricing. Russia stands to benefit from the shift, as constrained alternatives increase demand for its crude, particularly among price-sensitive buyers.

The U.S. decision also highlights the fragility of current ceasefire arrangements. The brief reopening of Hormuz raised hopes of normalization, but the rapid re-emergence of disruption indicates that maritime stability remains contingent on unresolved political and military tensions. For traders and refiners, that translates into persistent uncertainty around supply reliability.

The administration has not detailed the reasoning behind its reversal, but the timing suggests that market stability has taken precedence over strict adherence to earlier policy signals. Allowing a controlled flow of Russian oil offers a way to moderate price spikes and ease pressure on global inventories without formally easing sanctions on future production.

Still, according to energy analysts, the reliance on temporary waivers carries longer-term risks. This is because repeated adjustments can weaken the credibility of sanctions enforcement and create expectations that restrictions will be relaxed whenever markets tighten. That perception could complicate future efforts to use energy policy as a geopolitical tool.

For now, the extension is calibrated as a short-term intervention, tied specifically to cargoes already in transit. But it is seen as a reflection of a broader reality: in a market shaped by conflict in both Eastern Europe and the Middle East, policy is being driven less by strategic design and more by immediate necessity.

As long as the Strait of Hormuz remains unstable, the U.S. and its allies are likely to face recurring trade-offs between geopolitical objectives and energy security. The latest waiver is one such trade-off—an acknowledgment that, in the current environment, maintaining supply may require accommodating sources that policy was designed to constrain.

Impossible to Blockade Bitcoin: Strategy CEO Saylor Says Amid Iran’s Hormuz Crypto Toll Drama

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As geopolitical tensions rise around the Strait of Hormuz, one of the world’s most critical oil chokepoints, an unexpected narrative has emerged at the intersection of global trade and digital finance.

Iran’s reported move to explore cryptocurrency payments, including Bitcoin, for oil tanker transit has sparked intense debate about the future of money in conflict zones and sanction-heavy environments.

Amid this backdrop, Strategy CEO Michael Saylor has doubled down on Bitcoin’s core proposition, arguing that unlike physical infrastructure such as shipping lanes or traditional banking systems, Bitcoin cannot be “blockaded” or controlled by any single nation.

In a post on X, he wrote,

“Impossible to blockade Bitcoin”.

His comments highlight a growing belief among crypto advocates that Bitcoin’s borderless and censorship-resistant nature positions it as a resilient alternative in an increasingly fragmented global economy.

Saylor’s statement sparked reactions on X as supporters praised Bitcoin’s censorship resistance, calling it “digital gold” that has already surpassed physical gold in certain aspects.

Skeptics pointed out practical limitations, noting that  governments could still regulate exchanges, restrict internet access, or make fiat conversion illegal, effectively creating “soft blockades” for average users.

Several others noted that while the core network may be hard to stop, real-world access depends on electricity, internet infrastructure, and on/off-ramps.

Notably, the timing of Saylor’s speech could not be more relevant. As geopolitical tensions swirl around the Strait of Hormuz, the critical chokepoint through which roughly 20% of the world’s oil supply flows Iran has reportedly begun demanding transit tolls from oil tankers payable in cryptocurrency, with Bitcoin specifically referenced as a preferred option.

Bitcoin as Sanctions-Evasion Tool

During a fragile ceasefire in the broader US-Iran conflict, Iranian authorities, including spokespeople from the Oil, Gas and Petrochemical Products Exporters’ Union, have outlined a system where shipping companies must email cargo details and then pay a toll of approximately $1 per barrel in digital currencies often cited as Bitcoin within seconds.

The explicit goal is that payments that “can’t be traced or confiscated due to sanctions. This move highlights Bitcoin’s unique properties in high-stakes international trade:

Censorship resistance — No central authority can freeze or reverse transactions.

Borderless settlement — Value moves globally without relying on traditional banking rails vulnerable to sanctions.

Rapid Permissionless Transfers — Ideal for scenarios where speed and un-seizability matter.

While some analysts note that stablecoins have historically been more commonly used by Iranian entities for sanctions evasion, the public emphasis on Bitcoin underscores its growing perception as the ultimate “unblockable” asset.

Reports suggest the toll could reach millions of dollars per supertanker, potentially forcing shipping firms to hold or acquire Bitcoin for safe passage.

Bitcoin’s price has reacted positively to the news, surging amid heightened geopolitical awareness of its utility beyond traditional finance.

Broader Implications: Bitcoin in Geopolitics

Iran’s reported use of Bitcoin (or crypto more broadly) for Hormuz tolls is not just a sanctions workaround, it’s a live demonstration of Bitcoin as neutral, sovereign-grade money.

In a world of escalating financial warfare, assets that cannot be easily seized or blocked gain strategic importance.

Saylor’s post cuts through the noise that while governments can restrict access locally or attempt regulatory pressure, they cannot truly blockade the world’s first truly decentralized monetary network.

In an era of rising geopolitical friction, that resilience isn’t just theoretical. It’s being tested in real time in one of the world’s most vital shipping lanes.