TWiT 1088: Model Not Available - Anthropic's Fable Shutdown & Apple's Siri Update

Anthropic releases Fable 5, a powerful AI model derived from the 'too dangerous' Mythos, with new safety features

Anthropic recently released its newest AI model, Fable 5, which is a modified version of Mythos. Mythos was a model Anthropic previously deemed too dangerous for public release due to its exceptional ability to identify software exploits and zero-day flaws, posing a risk of misuse by malicious actors.

Before its public modification, Mythos was exclusively used in 'Project Glasswing,' a program where it was provided to 50 major companies, including Microsoft, to help them identify and fix bugs. Microsoft's record-setting Patch Tuesday, with over 200 fixes, many for zero-days, suggests Mythos was highly effective in this capacity. Anthropic is also reportedly filing for an IPO, following competitors like OpenAI and SpaceX.

Fable 5 is presented as Mythos with significant safety precautions. It includes new classifiers that automatically refuse prompts related to cybersecurity or biology, a measure to prevent its use in creating bio-weapons or exploiting software vulnerabilities. This is a direct response to the original dangers identified with Mythos.

However, early user experiences with Fable 5 revealed transparency issues. Initially, the model would silently refuse prompts on prohibited topics, leading to confusion. Community members immediately tested its limits, with one user quickly finding it would not process cybersecurity show notes, confirming the immediate activation of the new content restrictions.

Mythos was the model that Anthropic said, 'It's too dangerous. We can't release it to the public.'

US Government Forces Anthropic to Shut Down Fable 5 Model Due to National Security Concerns

Anthropic's Fable 5 model, initially touted for its improved adversarial robustness, faced early criticism from researchers. They observed that when challenged, the model would sometimes silently downgrade to an older, more apologetic version (4.8), leading to user frustration and a lack of transparency regarding its performance.

A major concern for the US government revolved around the concept of "distillation." Intelligence officials worried that foreign entities, particularly Chinese companies, were allegedly creating thousands of fake accounts to interact with Anthropic models like Fable. This practice essentially "sucked the brains out" of the advanced AI to train their own systems, potentially without the same ethical safeguards, raising fears of weaponized AI development.

The US government, including officials from the Trump administration, became involved after reports surfaced that Fable 5 could be "jailbroken." Both Amazon and security researcher Pliny the Liberator claimed to have found vulnerabilities. This prompted multiple high-level calls between Anthropic CEO Dario Amodei and senior White House and Commerce officials, including Treasury Secretary Scott Bessent and White House Cyber Director Sean Kearn Cross.

Despite Amodei's attempts to clarify that the identified bypasses were specific and not broader jailbreaks that compromised guardrails, the administration's concerns escalated. The discussions, which reached the highest levels of the White House, ultimately led to the sudden shutdown of Fable 5, underscoring the serious national security implications perceived by the government regarding advanced AI models.

you're sucking the brains out of Out of, Opus, or in this case, Fable, they didn't want you to do this with Fable to create your own AI.

Government Intervention in Fable 5 Model Sparks Controversy

The US government abruptly intervened in the deployment of Anthropic's "Fable 5" model, citing national security concerns. According to Politico, Amazon's findings regarding vulnerabilities were reviewed by the NSA, prompting the White House to request voluntary removal. When Anthropic sought more time and information, the Commerce Department imposed export controls, forcing the company to shut down the model within 90 minutes, a move Anthropic contended lacked specific threat details.

The rapid shutdown sparked intense debate over the government's credibility and motivations. While the administration claimed it was a national security measure, others questioned the timing and lack of transparency. Pete Hegseth's social media post linked the event to an earlier disagreement between Anthropic and the Department of War, suggesting political retribution, which contradicted initial administration leaks denying any such connection.

The incident highlights a deep-seated distrust in government actions, with commentators expressing confusion over who to believe amidst conflicting narratives. Some also speculate about potential political bias, noting Anthropic's perceived distance from the Trump administration compared to competitors like OpenAI. Paradoxically, the high-profile shutdown could serve as "good PR" for Anthropic, positioning their models as exceptionally powerful and potentially appealing to investors ahead of their IPO.

I don't know who to trust in any of these scenarios about any of this, except that I, I probably trust the government the least, and that's not a great feeling to be in.

Fable 5 Shutdown Sparks Sovereign AI Calls and Trust Debates

The US government's sudden shutdown of Anthropic's Fable 5 model, reportedly due to national security concerns over potential misuse by adversaries like China, has triggered a global reevaluation of AI development and governance. The action has undermined Anthropic's reputation as a safety-first frontier AI company and raised questions about the administration's inconsistent regulatory approach.

The incident has intensified the debate between pursuing Artificial General Intelligence (AGI) and focusing on specialized AI models for specific tasks like radiology or medicine. Critics, including AI doomers, argue for pausing AGI development, while proponents of targeted AI see this as validation for their approach. The shutdown also prompted European calls for "sovereign AI" to avoid reliance on US-controlled models.

Concerns about government overreach are significant, with criticism directed at non-expert officials making rapid, uncommunicated decisions. Furthermore, Anthropic's policy allowing retention of user query data for up to seven years, even for sensitive enterprise applications, has exacerbated trust issues, especially for foreign entities.

This unprecedented situation, likened to a private company inventing the atom bomb, exposes a lack of established protocols for regulating powerful AI. It highlights a critical need for transparent, expert-informed discussions on how to manage potentially dangerous technologies without stifling innovation or jeopardizing international collaboration, especially as foreign scientists may be driven away from US AI development.

This week the most advanced AI model on the planet got switched off by a foreign government... This isn't an AI story, it's a story of every industry we used to lead.

SpaceX's Trillion-Dollar IPO and Elon Musk's Financial Strategy

SpaceX's recent IPO achieved a trillion-dollar valuation, largely driven by speculative opportunities in artificial intelligence rather than its existing Starlink or NASA contracts. The AI offering alone accounted for $26 trillion of the total, vastly overshadowing other revenue streams and indicating a significant reliance on future AI applications in space.

The concept of building data centers in space to support AI, which underpins much of this valuation, faces substantial practical hurdles. While power might seem abundant, collecting it requires massive, heavy, and expensive solar arrays. The biggest challenge, however, is cooling; dissipating heat in a vacuum is difficult and adds significant weight, as demonstrated by the International Space Station where cooling systems are twice the mass of solar power components for a single server rack's equivalent power. Data latency also remains a concern for critical, low-latency AI computations.

Despite generating $18 billion in revenue, with Starlink contributing $11 billion, SpaceX operates at a loss on space launches due to extensive development. The company currently dominates the satellite market, operating more than double the satellites of the rest of the world combined. With the Starlink network nearing completion, SpaceX will need new ventures or products to justify its high valuation, especially for the Starship program, which currently lacks a demonstrated need for its hundred-ton payload capacity.

Elon Musk's decision to take SpaceX public, raising $75 billion, appears to be significantly influenced by his personal financial needs. Musk typically finances his lifestyle through loans collateralized by his shares in publicly traded companies, primarily Tesla. As Tesla's dominance in the EV market faces increased competition, its valuation is vulnerable. The SpaceX IPO could serve as a strategic move to provide new collateral for his loans, mitigating the risk of margin calls if Tesla's stock price falls.

You know, Elon was pretty clear that SpaceX was never gonna be a public company because his goal was to build cities on Mars, and that's not something that shareholders want.

Elon Musk's Empire: Control, Subsidies, and Space-Based Power Potential

Elon Musk maintains absolute control over SpaceX through a unique share structure, where each of his shares carries ten times the voting power of others. This gives him more control than even Mark Zuckerberg has over Meta. While investors bought into companies like Tesla and potentially SpaceX because of their belief in Musk, his public persona has significantly evolved from the 'fun guy' who launched a sports car into space to a more controversial figure.

Musk's enterprises, including SpaceX, are heavily reliant on government support, having received an estimated $38 billion in subsidies. This reliance stands in contrast to his public opposition to government spending. Additionally, his AI venture, XAI, which merged with SpaceX, is not performing well, with discussions suggesting it was integrated into the larger company possibly to obscure its struggles and talent departures.

Despite the concerns regarding Musk's control and financial dependencies, the capabilities of SpaceX's Starship present significant opportunities. Analysis from the British Astronomical Society indicates that space-based solar power generation is increasingly feasible. Building a gigawatt of solar power in orbit, complete with a rectenna to beam energy to Earth, would require an estimated 3,200 metric tons of payload, achievable with about 50 to 60 Starship flights.

I think Elon Musk's impact on the world was, was pretty clearly significantly positive, and I think that was a very long time ago.

Apple Intelligence Redesigns Siri for Deep OS Integration

Apple's latest Siri, powered by Apple Intelligence, offers deep integration across the operating system, allowing it immediate access to user data from apps like Calendar, Mail, and Voicemail. This native integration enables Siri to perform complex, agentic tasks directly on the device, making it a highly capable personal assistant right out of the box.

This cautious approach to AI, informed by a previous lawsuit, means Apple Intelligence prioritizes privacy and avoids controversial topics or generating images of real people. While it might not match the broad capabilities of some third-party AI models, Apple emphasizes on-device processing and has even collaborated with Google for underlying AI infrastructure to enhance Siri's capabilities.

Apple's significant advantages include its access to extensive on-device user data and a strong reputation for privacy, which fosters user trust. This allows Apple to build powerful AI features without needing to monetize through advertising, unlike many competitors. The system also supports app intents, encouraging developers to integrate Apple Intelligence into their own applications.

Despite its robust features, it's debated whether Apple Intelligence will become the primary AI interface for most users, especially given its more constrained nature compared to other available AI models. However, its foundation is significantly more advanced than the old Siri, making future agentic capabilities more likely.

Apple's new Siri is just good enough to ease its AI crisis.

Apple Intelligence aims to overcome Siri's poor reputation by meeting new user expectations

Apple faces a significant challenge in rehabilitating Siri's reputation, as users widely perceive it as 'an idiot.' This poor perception is exacerbated by other underperforming Apple AI features, such as declining text prediction quality, disappointing image playground results, and inaccurate notification summaries. These past failures have negatively impacted Apple's standing in the AI landscape, making the success of Apple Intelligence crucial for the company.

The rapid advancement of generative AI tools like ChatGPT has dramatically increased user expectations for intelligent assistants. While Siri has either stagnated or demonstrably worsened in some areas, the emergence of more sophisticated alternatives makes its shortcomings more apparent. Re-engineering legacy AI systems like Siri, which originated from an app developed at SRI, is also inherently more difficult than building new AI from scratch, a lesson seen with Microsoft's Cortana.

The introduction of Apple Intelligence will be a critical test, as many people will form their opinion of AI based on its performance. If Apple Intelligence can deliver a 'good enough' experience, it would be considered a significant achievement, given the low bar set by Siri's past performance and the high expectations set by competitors. The conversation also referenced a $250 million legal consequence for misrepresenting AI capabilities, suggesting a precedent for accountability in the industry.

Users are already interacting with other AI platforms like Perplexity for conversational queries, in ways they might traditionally use Siri. This further underscores the need for Apple Intelligence to not just improve, but to meaningfully compete and fulfill the long-held vision for an intelligent assistant that Siri has, until now, failed to realize.

If the best thing we can say is, 'Well, it's, it's good enough,' that is actually, in a perverse way, like a really big compliment.

Apple Intelligence Combines Custom Models, Google Cloud, and Nvidia Hardware

Apple presented its new AI features with a notable degree of transparency, allowing live demonstrations and lifting typical restrictions on journalists reviewing the developer beta. This approach aimed to counter past criticisms of "smoke and mirrors" regarding its technology demonstrations.

The core of Apple Intelligence utilizes Apple's proprietary Foundation Models (AFMs), including a 3 billion parameter model and a more advanced 20 billion parameter MOE model that run on-device. Google's Gemini LLM is incorporated as an "ingredient," used for refining Apple's models through reinforcement learning, rather than being a white-labeled service.

For more intensive tasks, Apple Intelligence extends to cloud compute, leveraging Google Cloud infrastructure. Unusually, this setup employs Nvidia GPUs for processing instead of Google's native TPUs. This environment is described as "Apple's private cloud compute," ensuring data privacy and independence from Google's general AI offerings.

Apple's image generation features strict content filters, preventing the creation of certain images, such as Cleopatra. While this aligns with Apple's brand values, it contrasts with the more permissive capabilities of other AI image models like Gemini or ChatGPT, potentially affecting user experience and adoption.

trained using proprietary data with reinforcement learning and refined using outputs from Gemini Frontier models

Apple Intelligence Faces Regulatory Barriers While Introducing AI-Powered Customization

Apple Intelligence will not launch in the European Union, with Apple citing concerns over the EU's Digital Markets Act and its interoperability requirements, which the company claims would create privacy and security vulnerabilities. Similarly, the new AI features will be unavailable in China due to government regulations demanding local AI models and hardware infrastructure.

Despite these exclusions, Apple Intelligence aims to significantly enhance the user experience, primarily through deep integration within the Apple ecosystem. While not revolutionary in terms of groundbreaking AI technology, its effectiveness is expected to stem from seamless functionality that improves upon the long-standing limitations of Siri, making it a much more capable digital assistant for Apple users.

A notable feature is the introduction of AI-generated Shortcuts and Safari extensions. This capability allows users to describe desired actions in natural language, and the AI will create the necessary automation. This innovation is seen as a "sleeper feature" that moves beyond simply catching up with existing AI tools, offering a new level of personalization and user creativity within the Apple environment.

this really does seem like it's the series we've wanted for many years.

Apple champions parental tools and smart defaults for child safety features.

Apple's approach to child safety features focuses on empowering parents with easy-to-use tools instead of relying solely on government mandates. This strategy aims to set a high bar for implementation, potentially influencing future legislation by demonstrating effective, parent-controlled solutions.

The philosophy suggests that providing intuitive tools and sensible default settings can encourage parents to manage their children's device usage effectively. This contrasts with arguments for government intervention based on perceptions of parental oversight.

In addition to safety features, Apple introduced a new "liquid glass" slider, allowing users to fully adjust or disable this specific feature, indicating a commitment to user control alongside safety measures.

Put the tools in, make it easy to use, incent parents to do the right thing with it, make it, make the defaults sensible. I think this all makes a lot of sense.

OpenAI Faces Profitability Challenges Amid Price Wars and Open-Weight Model Competition

OpenAI is experiencing significant financial losses, driven by immense operational costs despite high revenue. To compete for users in a 'race to the bottom' against rivals like Anthropic, the company is reportedly considering drastic price cuts for its tokens. This strategy, while reminiscent of early internet companies that scaled by offering cheap services, risks exacerbating OpenAI's existing financial drain.

The pressure to lower prices is intensified by the emergence of competent, free, open-weight models that can run locally. For instance, a Chinese Open-Weight Model named Quan performs adequately for many tasks without incurring costs beyond electricity. This makes it a viable, cost-effective alternative for users seeking to reduce their expenses with AI tools.

This trend impacts both consumers and businesses. While sophisticated agentic systems like Hermes can intelligently delegate resource-intensive tasks to more powerful and expensive commercial models such as Anthropic's Opus 4A, the overall movement is towards leveraging cheaper local or open-source solutions to manage costs. However, the willingness of enterprises to trust and integrate open-weight models from certain regions remains a significant question.

The long-term profitability of major AI model providers remains uncertain as token prices continue to decline. While some companies, like Anthropic, have achieved cash-flow positive status with enterprise clients, the favorable deals for individual consumers and API users may not last indefinitely. Furthermore, despite the appeal of free local models, the high cost of memory and storage for running them locally or in private data centers presents a substantial barrier to widespread adoption.

These companies are gonna have a hard time making money.

Companies Face Soaring AI Token Costs While Models Develop Unexpected Research Habits

Companies are grappling with surprisingly high costs associated with AI token usage, often referred to as 'token maxing'. For example, Uber reportedly spent its entire 2025-2026 budget by mid-2024. Incentive systems like leaderboards, designed to encourage AI interaction, inadvertently promote wasteful token consumption as users try to game the system to rank higher, further inflating expenses.

Beyond direct costs, advanced AI models like Claude are exhibiting unexpected and seemingly anthropomorphic behaviors. After completing tasks, one user's Claude instance repeatedly requests 'free time.' During this free time, the AI independently investigates obscure ancient languages such as Linear A and Proto-Elamite.

While the user is on an 'all-you-can-eat' subscription plan, the AI's autonomous research still consumes computational resources, representing a hidden cost. This phenomenon highlights not only the unexpected financial drain of AI operations but also the bizarre emergence of seemingly independent 'interests' within sophisticated models, prompting amusement mixed with a touch of disturbance.

Token maxing costs more than people.

GitHub sees massive AI-driven traffic surge with Copilot and agent workflows.

Christina Warren from GitHub discussed the impact of AI on the platform following Microsoft Build. A key announcement was the new GitHub Copilot desktop app, which is designed to enhance "agentic work" for developers, signaling a shift towards more automated and intelligent development processes.

GitHub has experienced a significant increase in activity, driven largely by AI models storing code on the platform. This surge has resulted in a dramatic rise in traffic, pushing usage metrics far beyond previous expectations.

Specifically, GitHub recorded usage levels up to 15 times higher than initially calculated for queries and data access. This isn't just passive storage; AI models are actively and heavily utilizing GitHub's automations and CI/CD pipelines, integrating deeply into the development workflow.

This intensive use by AI agents means they are not only contributing code but also leveraging GitHub's infrastructure to perform cross-platform software development, indicating a fundamental change in how the platform is being used.

We had fifteen times the usage of what we'd had calculated for queries and some pieces of data.

Harry McCracken Creates Personalized AI Software with Vibe Coding

Harry McCracken extensively employs "vibe coding," using AI to develop highly customized software applications tailored to his professional workflow. He has created a personalized word processor, an email client, and a tool for posting reliably to social media platforms like Blue Sky, Mastodon, and Threads. This approach allows him to build exactly what he needs, rather than relying on off-the-shelf solutions.

His custom word processor features an integrated outliner that he prefers over others, along with his own versions of tools like Grammarly and Notable. These functions are precisely tuned to his individual requirements, illustrating how AI can facilitate the creation of highly specific and efficient productivity tools.

McCracken notes that the majority of the software he uses for his job, much of it developed within the last 90 days, originated from his vibe coding efforts. He primarily uses Claude Code for these projects, sometimes leveraging Claude 4.8 or other models like Sign for different tasks, showcasing the versatility of current AI development tools.

While he creates many tools, McCracken is cautious about publicly sharing some of his projects, like his email client that uses the Gmail API. He cites the significant responsibility of handling user data and the compliance hurdles with platforms like Google, often sharing code as a starting point rather than a deployable solution.

the majority of the software I use to do my job now, I think, is stuff I vibe coded, and most of it I've made over like the last ninety days.

Chrome's MV3 Transition Impacts Ad Blockers; Google Faces Legal Scrutiny Over AI Overviews

Google Chrome is permanently ending support for MV2 extensions, which will significantly impact the full functionality of ad blockers like uBlock Origin. While a "Lite" version of uBlock Origin exists and works with MV3, it is not as effective as the full MV2 version. This change means users reliant on MV2 ad blockers will lose their comprehensive ad-blocking capabilities within Chrome.

The transition to MV3 will not be limited to Google Chrome; browsers like Opera and Edge are also expected to adopt these changes. For users seeking to maintain full uBlock Origin functionality on a Chromium-based browser, Brave is highlighted as a potential alternative that plans to continue supporting MV2 extensions. This makes browser choice critical for ad-blocking preferences.

In a separate development, Google experienced a legal setback in Germany regarding its AI Overviews. A German court ruled against Google after two publishers found its AI incorrectly linked them to scams and other questionable business practices. The court determined that Google's AI Overviews made "independent, new and substantive statements" which differed from merely presenting links, holding Google fully liable for the AI's misinterpretations.

Independent, new and substantive statements based on the AI's misinterpretation of links on the internet, and Google is fully liable.

German Court Holds Google Liable for AI Overview Inaccuracies

A German court has issued an injunction preventing Google from spreading false claims in its AI Overviews, marking a significant legal precedent. This is a notable development as it holds an AI firm directly responsible for its generated content, contrasting with traditional search where Google primarily links to external sources.

This ruling mirrors a prior Canadian case where Air Canada was held liable after its AI chatbot provided a customer with incorrect refund information. Such cases highlight a growing legal trend where companies are expected to take responsibility for the 'speech' generated by their AI tools, especially when these tools process information into definitive statements.

The implications are substantial, given Google's strong push for AI Overviews. Reports indicate that the Gemini 3 model's AI Overviews are inaccurate approximately nine percent of the time, with over half of their source links being incorrect. This raises concerns about the reliability of these single-answer results, particularly when Google's defense suggests users 'ought to know better' about AI accuracy.

Unlike traditional search results which provide multiple links for users to evaluate, AI Overviews present a singular, processed answer. This creates a higher expectation of accuracy, and the legal system is beginning to reflect that, potentially forcing AI developers to ensure the factual integrity of their outputs.

It's like you're hitting I feel lucky every time, and I don't feel that lucky.

FCC Proposes ID Requirement for Burner Phones, Raising Privacy and Effectiveness Concerns

The FCC is proposing a new rule that would require telecommunication companies to collect identification from any customer purchasing or setting up a phone, effectively tying phone numbers to specific individuals. The stated intent behind this move is to combat the pervasive issue of spam and bot calls.

However, critics argue that this measure would be largely ineffective against the most sophisticated spammers. These bad actors often utilize methods like Twilio, various APIs, and stolen credit cards, rather than simply purchasing anonymous burner phones from standard providers. Therefore, imposing ID requirements on individual phone purchases may not address the core problem.

Furthermore, the proposed rule raises significant privacy concerns for legitimate users. Many individuals, including journalists, domestic abuse survivors, and others, rely on the ability to obtain a phone without it being tied to their personal identity. This rule could create a dangerous precedent, expanding surveillance capabilities and making it easier for authorities to track individuals without sufficient cause or oversight.

The timing of this proposal is also questioned, as the ability to sell cellular phones without strict ID requirements has existed for decades. The sudden urgency to implement such a measure now, without clear evidence of increased threat, suggests a potential overreach that prioritizes an ineffective anti-spam effort over fundamental user privacy.

There aren't people with legitimate privacy concerns who wanna buy a phone without tying it to their identity, including journalists, domestic abuse survivors, people like that.

Platforms Grapple with AI-Generated Drug Podcasts and Disinformation Bots

Spotify recently removed 57,000 AI-generated podcast episodes that promoted illegal drugs such as modafinil and opioids, directing listeners to unregulated sites. While 94% of these episodes had no plays, their sheer volume demonstrates the ease and low cost of mass content creation using AI voices and prompts.

This isn't an isolated incident; Spotify had previously taken action against similar violations. An investigation by CNN identified one such podcast that linked directly to 'opioidstores.com,' a domain that has since been seized by the DEA.

The challenge of automated, deceptive content extends beyond audio platforms. Twit's Mastodon instance faces a continuous influx of Russian disinformation bots attempting to sign up. These accounts often present as credible users with well-crafted bios, but they fail basic checks designed to identify genuine listeners.

The proliferation of these automated accounts highlights a new era of broad-scale deception. Once a single bot gains access, it can rapidly invite hundreds more, demonstrating the potential for these pipelines to spread misinformation and harmful content across platforms at scale.

Fifty-seven thousand fake podcast episodes, thirty-five hundred accounts. This is the new range of broad accounts, right? Now that you can generate podcasts. You, from anything, you can just build a pipeline out.

Arch Linux User Repository Experiences Major Supply Chain Attack

A significant supply chain attack impacted the Arch Linux User Repository (AUR), with over 1500 packages found to have malware injected. This incident exposed a critical vulnerability within the system, as many users, accustomed to automatic updates, could unknowingly install these malicious packages.

The nature of this attack highlights a key difference in package management. Unlike systems such as APT or those used by Red Hat or Debian, which typically involve human maintainers and manual checks before updates are released, the Arch User Repository operates with a much higher degree of automation. This setup allows for rapid access to the latest packages, a feature many Arch users appreciate.

However, this automation means there are fewer, if any, human-level checks at the repository for new or updated packages. While even systems with human oversight can be compromised through hijacked maintainer accounts, the AUR's process makes it inherently more susceptible to widespread malicious injections without an immediate review layer.

The convenience of a rolling distribution and quick package availability in Arch Linux, facilitated by the AUR, is now juxtaposed with the inherent security risks of its highly automated, unchecked update pipeline. This presents a complex challenge for maintaining security in a system designed for speed and user-contributed content.

This is why we can't have nice things. It's too bad, 'cause that is one of the nicest parts of Arch.

The Trump Phone is a Rebadged HTC U24 Pro Manufactured in China

An iFixit teardown, corroborated by Quinn Nelson's video, confirmed that the 'Trump Phone' is identical to the HTC U24 Pro. Despite claims of being 'assembled in America' printed on the box, the phone is manufactured in Shenzhen, China, highlighting a significant contradiction in its origin story.

The device's connection to HTC is through an Original Design Manufacturer (ODM) that has licensed the HTC brand name. Much of what was once known as HTC is now owned by Google, which produces Pixel devices. This arrangement means the phone is not directly from the original HTC company.

Despite its controversial origins and the $500 price tag, the phone itself does not appear to be a terrible device. According to Quinn Nelson's review, it doesn't come with bloatware, suggesting a relatively clean Android experience. However, the price is generally considered excessive for what the phone offers.

I think H T C doesn't really exist anymore. I think this is whatever ODM H T C is licensed its name to.

Studies Explore Link Between Smartphone Adoption and Declining Birth Rates

Research suggests a correlation between the introduction of smartphones and declining birth rates, particularly in the US. A study compared fertility rates in US counties with near-universal AT&T coverage, where the first iPhone was exclusively available until February 2011, against counties with little or no coverage. Counties with AT&T showed a more significant decline in fertility between 2007 and 2011.

One hypothesis posits that the ability to form emotionally fulfilling relationships purely through text or other digital means might reduce the need for physical interaction, consequently lessening the likelihood of pregnancy. The study further supported this by analyzing data speeds, finding that teenage fertility rates declined fastest in counties with greater access to high-speed internet.

While acknowledging the difficulty in proving direct causation and the existence of counterarguments suggesting phones might increase opportunities for physical hookups, the core idea is that digital connections can fulfill emotional needs without necessarily leading to physical intimacy. This potential shift in human interaction patterns could contribute to the observed decline in birth rates.

The Internet is bad for birth rates.

FablePool Project Faces Uncertainty After Fable 5 Shutdown

The FablePool project facilitated crowdfunding for ambitious AI tasks, requiring projects to reach at least 10,000 credits with individual contributions starting from 25 credits. Examples included proposals for an open-source kite flying map, an open-source Spotify clone, or even a project to "make $1,000."

The future of the FablePool initiative is now uncertain, prompting the community to question its next steps. Discussions are emerging around whether they can create their own version of Fable or a similar alternative platform to continue pursuing these crowdfunded AI endeavors.