In this Tekedia Daily video podcast, I present a compelling argument for a balanced approach to wealth building that prioritizes both strategic saving and smart investing. The host begins by challenging the common “invest, invest, invest” mantra often found in online finance content. The core thesis is that while investing is essential for long-term growth, an overemphasis on immediate investment can be a strategic mistake.

He argues that a critical component of a successful financial strategy is the ability to save strategically, accumulating liquid capital to seize timely opportunities. He provides a vivid example of a market downturn where a valuable asset becomes available at a low price; without cash on hand, an investor would be unable to capitalize on this opportunity.

The presentation then delves into a breakdown of three key investor types: the Income Chasers, who seek consistent returns from dividends and bonds; the Growth Makers, who take on significant risk for high-growth startups and hedge funds; and the Value Pickers, who strategically acquire undervalued assets during market turmoil, drawing on historical examples like John Templeton and Carlos Slim. This categorization helps the listener understand different investment philosophies.

The speaker concludes by forecasting a coming economic recession, which he frames not as a negative event but as a fertile ground for opportunity. He supports this prediction with insights from a US banking executive, citing rising credit card delinquencies, and the impact of student loan defaults on credit scores. He emphasizes that these localized economic pressures, coupled with a globally interconnected system, will lead to a broader market reset.

The central takeaway is that those who have strategically saved and have liquid capital ready will be in the best position to deploy that capital and reap the rewards during the coming economic shift. The final message is a call to action: save for the opportunity and then deploy that capital with a clear investment thesis that aligns with your financial goals and expected returns.

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OpenAI CEO Sam Altman says the world is still far away from artificial general intelligence (AGI), despite the release of GPT-5, the company’s most advanced AI model yet.

According to Altman, while GPT-5 marks a significant leap in capability and general intelligence, it still falls short of what could be considered true AGI — a system that can match or exceed human reasoning across the board.

Altman, who has been one of the most vocal proponents of AGI development, stressed that OpenAI’s core mission to build artificial general intelligence that benefits all of humanity remains unchanged. However, he acknowledged that GPT-5, despite its power and versatility, still lacks several key features that he believes are essential to AGI.

Among those missing pieces is the ability to learn continuously from its environment. “This is not a model that learns as it’s deployed,” Altman noted, calling that absence one of the major indicators that OpenAI has not yet reached AGI.

He emphasized that the system does not improve itself dynamically by drawing from real-world interactions after training — something he sees as critical to what would qualify as general intelligence.

To understand the weight of Altman’s comments, it’s worth looking at how far the company has come. The first iteration of GPT, short for generative pre-trained transformer, was released in 2018, offering modest capabilities in text generation. Then came GPT-2 and GPT-3, with exponential improvements, culminating in GPT-4, which stunned the world with its ability to write, reason, code, and hold nuanced conversations. GPT-5 builds on all of this, introducing multimodal abilities, broader context windows, and a significantly more fluid understanding of human language and intention. Yet, even with all of that, Altman says there’s something missing — or many things.

The comments come at a time when debates around AGI are becoming more intense, with some voices warning that the tech industry is rushing blindly into a future it doesn’t fully understand, while others remain skeptical that AGI is anywhere close. Altman’s assessment threads the needle between optimism and caution. He says GPT-5 is a major step forward, “a significant fraction of the way to something very AGI-like,” as he put it, but not the finish line.

He also pointed to what comes next: superintelligence. For Altman, AGI is not the ceiling — it’s a milestone. His broader vision includes the creation of tools that not only think like humans but vastly outthink them, systems that could accelerate scientific breakthroughs and reshape the future of civilization.

What’s Under the Hood of GPT-5

GPT5 is a unified system with multiple internal models — a fast responder, a deeper reasoning variant, and a high-capacity “thinking-pro” edition. A real-time router dynamically selects the best model for each query, effectively replacing the need for users to manually pick the right tool for the task. Variant tiers — regular, mini, and nano — cater to different usage needs and budget levels.

In ChatGPT, GPT-5 is accessible to all users:

• Free tier: Standard GPT-5 with usage caps and automatic fallback to GPT-5 mini when limits are hit.
• Plus users: Higher usage thresholds and selectable access to “GPT-5 thinking.”
• Pro tier ($200/month): Unlimited access, including the more powerful “GPT-5 Pro.”

Developers using OpenAI’s API can choose among models scaled for cost, from full GPT-5 to budget-friendly nano options, with input/output token pricing that varies accordingly.

What’s Improved

OpenAI claims GPT-5 delivers state-of-the-art performance across domains:

• In coding, it excels at building responsive UIs, debugging large codebases, and executing long, agentic tasks.
• In writing, it handles structural ambiguity and literary nuance with greater fidelity.
• In health, it acts more like an active thought partner, probing context, flagging concerns, and scoring well on benchmarks like HealthBench.
• It also achieves top marks in math, science, vision, and multimodal reasoning.

Industry critics believe GPT-5 represents a pivotal shift in usability — a model that now truly feels like interacting with a PhD-level expert across domains. It also sets a new standard for practical, versatile AI assistance. Yet as OpenAI emphasizes, ambition remains on superintelligence — a theoretical level of AI exceeding human capacity and transformative potential in science, innovation, and society.

Nvidia’s Chief Security Officer, David Reber Jr., has issued a strong public denial of claims suggesting the company’s chips contain secret backdoors or kill switches, saying, “there is no such thing as a ‘good’ secret backdoor—only dangerous vulnerabilities that need to be eliminated.”

His remarks come as the company finds itself under growing pressure from both sides of the geopolitical divide, with US lawmakers advocating tighter control over chip exports and Chinese officials accusing the chipmaker of embedding covert access mechanisms in its AI hardware.

“To mitigate the risk of misuse, some pundits and policymakers propose requiring hardware ‘kill switches’ or built-in controls that can remotely disable GPUs without user knowledge and consent,” wrote Reber Jr. “Some suspect they might already exist,” he continues, in a nod to a probe already launched in China over alleged “loopholes and backdoor” vulnerabilities in the H20 chips that have been sold in the country.

The controversy stems from a convergence of domestic political pressure in the United States and intensifying scrutiny from China. In May, a bipartisan group of US lawmakers introduced the Chip Security Act, legislation that would require AI chipmakers like Nvidia to include embedded tracking systems capable of identifying unauthorized exports and potentially disabling hardware remotely. Though pitched as a national security safeguard, the bill leaves open the possibility of adding kill switches—components that could render the chips inoperable from afar.

While the bill is still in early legislative stages, it has already sparked concern among global buyers, especially in China, where regulators have accused Nvidia of secretly inserting such mechanisms into its AI chips. The allegations culminated in a public summons by Beijing’s cybersecurity watchdog, which demanded an explanation over what it described as “loopholes and backdoor” vulnerabilities in Nvidia’s H20 chips—products that were specially redesigned for China after Washington banned the sale of its most powerful AI processors, such as the A100 and H100.

The H20 chips were developed as a workaround to the US export restrictions imposed in 2022 and further tightened in 2023, which aimed to slow China’s progress in artificial intelligence and supercomputing. After months of review, the US government approved the H20 for limited export to China, signaling a green light for Nvidia to re-enter a lucrative market that had once been its largest revenue generator outside the US.

However, Beijing’s approval came with strings attached. Upon allowing the import of the modified chips, Chinese regulators initiated a technical review to ensure the chips did not contain any features that would allow them to be tracked, controlled, or shut down remotely. Officials in Beijing have warned that such components would constitute a national security threat and violate China’s sovereignty.

The probe is ongoing, and analysts say it underscores China’s deepening mistrust of US technology providers in the wake of broader Washington sanctions and scrutiny against firms like Huawei and TikTok.

Reber Jr.’s blog post appears to be a strategic defense against growing doubts from both Washington and Beijing. Addressing US policymakers directly, he wrote that mandatory kill switches would be “an open invitation for disaster” and “not sound policy.” His comments suggest that Nvidia is caught in a precarious position, attempting to reassure lawmakers in Washington of its compliance while also trying to calm fears in Beijing that it could be used as an extension of US intelligence interests.

AI chip sales are driving Nvidia’s explosive growth, and its ability to operate in China, still the world’s second-largest economy, could determine whether it remains dominant in the long run. But that dominance is now under threat. China is fast-tracking its own semiconductor ecosystem, with firms like Huawei rapidly advancing domestic alternatives to Nvidia’s technology. Analysts say that if Chinese regulators conclude that Nvidia’s chips are compromised or politically risky, it could accelerate Beijing’s decoupling from US tech suppliers.

Ironically, Huawei’s own fall from grace began under similar suspicions—that it had built backdoors into its telecom equipment for Chinese government access. Now the tables are turning, with Chinese regulators warning that it is Nvidia who may be giving foreign governments covert entry points into critical computing infrastructure.

Both Washington and Beijing appear determined to bend Nvidia’s business to their respective strategic goals. The US wants guarantees that its chips won’t fall into the hands of adversaries, while China wants assurance that US tech won’t be used as a geopolitical Trojan horse. Caught in the middle, Nvidia is trying to convince both sides that its hardware is neutral and secure—a hard sell in today’s fractured tech landscape.