Empathy, according to Elon

Elon Musk: The fundamental weakness of Western civilization is the empathy exploit

"There's a guy who posts on the internet who's great, Gad Saad, and he talks about basically suicidal empathy. There's so much empathy that you actually suicide yourself. So we've got civilizational suicidal empathy going on.

I believe in empathy. I think you should care about other people, but you need to have empathy for civilization as a whole and not commit to a civilizational suicide.

The fundamental weakness of Western civilization is empathy. The empathy exploit. They're exploiting a bug in Western civilization, which is the empathy response.

I think empathy is good, but you need to think it through and not just be programmed like a robot. Its weaponized empathy is the issue."

From an Elon Musk podcast interaction with Joe Rogan in 2025 (@1:33:00). CNN news article on the topic here.

 

One scarcely knows where to begin in light of this level of ignorance. I randomly ran across this news item:

 

 

Below, a tweet by an equally clueless Elon-Bro' 

 

SMH...

Pedantically: "Empathy" is NOT s synonym for "sympathy." It refers to one's relative ability to accurately and precisely perceive the world as others do. There are 3 recognized sorta venn-diagram-overlapping clinical substrates: [1] cognitive, [2] affective, and [3] somatic.

 

More ASAP. Spent the entire day on Regime Change. Almost done.

 

UPDATE: OFF-TOPIC ERRATUM

 

The dual earthquakes in Venezuela are so horrifically, tragically sad. The death toll is sure to go well into 5 figures. Nearly 1,000 confirmed dead already, with 51,000 people reported as still missing.

 

Nasdaq: SPCX launch

Whatever. OpenAI, Anthropic, and other huge AI IPOs are soon to follow.

 

From the SPCX SEC.gov S-1 IPO filing form. 

MISSION STATEMENT 

To build the systems and technologies necessary to make life multiplanetary, to understand the true nature of the universe, and to extend the light of consciousness to the stars.

A BIT OF S-1 DETAIL COMMENCING ON PG. 194

AI
Grok
Grok represents a core pillar of our mission to advance humanity’s understanding of the universe through the development of truth-seeking artificial intelligence. Grok is designed and optimized for rigorous reasoning, real-time information synthesis, and transparent outputs, with a product philosophy centered on intellectual honesty, first-principles thinking, and engagement with complex topics.

Grok is designed as a truth-seeking AI model, built on our founder Elon Musk’s mission to enable humanity to understand the universe. We believe that accomplishing this mission requires a truth-seeking approach to AI. 

We define truth seeking as the active, relentless pursuit of what is objectively true about reality, and grounded in evidence, logic, empirical data, and first principles thinking. Our goal is to understand and explain what the universe appears to be doing, as accurately as current knowledge allows. In pursuit of this truth-seeking objective, Grok also enefits from its integration with X, our real-time information, entertainment, and free speech platform. This direct, real-time access to the information and human discourse on X enhances Grok’s truth-seeking capabilities by grounding outputs in up-to-date knowledge and diverse viewpoints.

Since the initial release of Grok 1, we have iterated rapidly, releasing Grok 2, Grok 3, and, the current version, Grok 4, each delivering material improvements in pre-training, reasoning depth, multimodal capabilities, latency, and scale. Building on this trajectory, we expect to continue scaling Grok through subsequent generations. 

Ongoing  training of next‑generation models is expected to scale toward multipletrillions of parameters, which could represent a step change in reasoning in depth and overall intelligence. In this context, the number of parameters refers to the scale of the model, where parameters are the internal numerical values, such as “weights,” that are adjusted during training to enable the model to recognize patterns and relationships in data. A larger number of parameters generally allows the model to capture more complex relationships, store greater amounts of knowledge, and achieve higher levels of reasoning capability. Our accelerated development cadence positions Grok among the fastest-advancing frontier models relative to peers, including OpenAI, Anthropic, and Google. Grok is differentiated by its emphasis on real-time data integration, particularly through insights derived from the X platform (subject to some limitations for certain content), enabling dynamic awareness of current events and user discourse, as well as by explicit investment in reasoning transparency and explainability. Grok enhances the X ecosystem by improving content understanding, personalization, and recommendation systems, thereby increasing user engagement and platform intelligence. We are currently developing next-generation iterations, including Grok 5, which are expected to further expand reasoning fidelity, multimodal integration, and domain-specific performance. 

Terrestrial AI Compute
Our terrestrial AI compute forms the backbone of the Grok model family and is anchored by the COLOSSUS and COLOSSUS II data centers that boast some of the world’s largest and most advanced AI training clusters. COLOSSUS and COLOSSUS II collectively provide approximately 1.0 gigawatt of compute power, with the additional power capacity available for data center operations. We brought the first cluster of COLOSSUS online in 122 days, repurposing the shell of an existing factory, and the first cluster of COLOSSUS II online even faster in 91 days. As an illustrative comparison, an industry benchmark to bring online a 100 megawatt greenfield data center is approximately two years. We also demonstrated a significant improvement in cost efficiency, achieving data center construction costs for COLOSSUS II that are considerably lower than industry benchmarks on a per megawatt basis. COLOSSUS II is capable of operating entirely by our self-built behind-the-meter gigawatt-scale natural gas power plant. Our data centers are integrated with the world’s largest Megapack deployment, providing additional layers of reliability and operating performance. At all our existing data centers we have employed a brownfield retrofit strategy leveraging existing industrial sites, advanced direct-to-chip cooling to support higher rack densities, and high-speed networking. The clusters deploy leading-edge GPUs to maximize training throughput and model performance. The next phase of expansion at COLOSSUS II is designed to train our next-generation Grok 5 AI model. As we continue to expand our AI compute infrastructure, we will also continue to enhance our power capabilities utilizing a combination of grid-power and behind-the-meter natural gas power plant buildouts. At COLOSSUS, our grid power capabilities are designed to purchase power from the grid as available, and to rely on our behind-the-meter, self-generated power and Megapack installations when grid power is curtailed.

X Platform
X is a real-time information, entertainment, and free speech platform that serves as a foundational distribution and data engine for our AI ecosystem. With a global user base generating substantial volumes of content at all times across a wide variety of topics, X provides a uniquely dynamic data for model training and real-time context integration, subject to some limitations for certain content, which significantly differentiates Grok from the other frontier lab offerings.

X is our real-time information, entertainment, and free speech platform that serves as a global town square with integrated AI capabilities powered by Grok. Designed to evolve toward an “everything app,” X enables users to post content, share media, engage in conversations, host, view, and participate in live group discussions, follow real-time events, use encrypted messaging, and leverage advanced features such as Grok-assisted post creation, content discovery, and conversational AI directly within the interface via the prominent Grok icon.

With native integration of Grok’s frontier models, including real-time access to X data for up-to-date insights, trending analysis, and enhanced search, X delivers personalized feeds, smarter recommendations, and low-latency AI assistance for our users worldwide. Our X Premium subscription options, including Basic, Premium and Premium+ tiers, offer expanded features, ad-reduced experiences, and priority Grok interactions. In 2023, Grok’s chat functionality was integrated into the X app allowing for the user to open the chat interface to type prompts and get real time answers.

Public X data enhances Grok’s training and reasoning capabilities, while the platform continues to deliver measurable performance outcomes for advertisers, with an increasing strategic focus on performance-based marketing solutions.

In addition to X consumer products, X offers advertisers and developers a powerful suite of tools to reach highly engaged audiences. Advertisers can target audiences through diverse ad formats—such as Promoted Ads, Vertical Video Ads, Collection Ads, and premium options such as X Amplify and Takeoversblending seamlessly with organic content for authentic engagement. With advanced targeting based on public conversations, events, keywords, interests, locations, and look-alike audiences, brands can connect with audiences while benefiting from flexible, performance-based pricing (pay only for actions such as clicks or engagements) and often lower costs compared to other platforms. We expect that our ongoing innovations—including Grok-powered integrations, new contextual ad tests, and expanded aspect ratio support for easy reuse of ad creative—make X a competitive choice for driving traffic, conversions, and brand awareness and visibility among X’s hundreds of millions of MAUs. Developers have access to a continuous, high-volume, real-time stream of data around current events, trends, or sentiment, which they can access through an official X Developer Platform and APIs.

In April 2026, we began a phased roll-out of our new advertising platform, that we rebuilt from the ground up. The new Ads Manager is built to help advertisers launch better campaigns, faster, with stronger ROI. Powered by AI, the new systems enable more precise, relevant and dynamic ad delivery. Ads are seamlessly integrated into a User’s X feed….

Bring a Snicker's, you're gonna be a while.

 

UPDATE 

 

Pardon my dubiety.

 

Read THIS book.

Also see "Something New, Something Old."

Karen Hao AI concerns. And, Anthropic frets over AI "autonomous recursive self-improvement."

Karen Hao, MIT-trained engineer and author of Empire of AI, who interviewed over 260 people including 90 OpenAI employees, warns that the AI industry needs to add close to the entire annual energy output of the UK to the global grid within five years, mostly through fossil fuels, that two-thirds of new AI data centers are being built in water-scarce areas, and that Elon Musk's Colossus supercomputer in Memphis is powered by around 35 unlicensed methane gas turbines. She details Kenyan content moderators paid a few dollars an hour to process the worst content on the internet until they developed PTSD, describes a proposed 10-year moratorium on state-level AI regulation being inserted into US legislation, and warns that on the current trajectory the next 20 years will end democracy, with Silicon Valley increasingly promoting the idea that corporate structures with CEOs at the top should replace democratic governance entirely. 

ANTHROPIC "RECURSIVE AUTONOMY" ANXIETY

 

From their "Institute" website.

Possible futures
What happens next depends on two things: whether the trend continues, and what we choose to do if it does. We can imagine at least three future scenarios:

1. The trend stalls, but today’s AI capabilities are widely diffused. This article features many exponential trajectories. But these trajectories may actually turn out to be S-curves. We may be approaching the bend in the curve, where returns to scale diminish and the line straightens, then flattens. The judgment that separates a competent researcher from a great one might be a capability that cannot come from scaling up training inputs like compute and data. If so, getting past this bottleneck would require a new idea, like an architectural approach that supplants the Transformer architecture that all current frontier models use.



Alternately, the binding constraint to AI progress could be in the supply chain, not the model: advancing and diffusing the frontier may require more energy and compute than presently exists. The pace of chip fabrication, grid expansion, or interconnect bandwidth may be the constraint, rather than intelligence itself. We also cannot rule out an exogenous shock to the AI ecosystem that dramatically slows things, like a sudden diminishment in the supply of compute or electricity, either of which would slow progress and make forward investment by labs more expensive. Or we may not be anticipating some other barrier to progress.



Even if model capabilities were frozen at today’s level, we would expect major changes to occur in the world. Project Glasswing is one early sign: in its first weeks, Mythos Preview found more than ten thousand high- and critical-severity software vulnerabilities across the world’s most important systems—enough that the bottleneck in cyber defense has already shifted from finding vulnerabilities to patching them fast enough. And we are still early in the diffusion of today’s models into the wider economy, where a 100-person company can increasingly do the work of a 1,000-person one, because each employee will sit atop a pyramid of agents.



We include this scenario for completeness, but we don’t believe it’s likely. Every capability we can measure, including those that feel “squishier,” like quality of code and success on open-ended tasks, has so far followed the same curve. We have not yet seen that curve bend. Of the three futures we consider, this one would give governments and societies the most time to adapt. We are more worried about the next two, which would move faster and leave far less room for preparation.


2. AI labs continue to see compounding efficiency gains. In this scenario, AI development becomes substantially automated, but humans continue to set research directions and judge results. Organizations that use AI systems would become much more efficient as time goes on, so we could expect to see significant productivity multipliers on each person in this organization. 100-person companies could do the work of 10,000- or 100,000-person organizations. This would revolutionize knowledge work and government services, but could also be turned to harmful ends, from authoritarian surveillance of whole populations to influence operations that tailor manipulation to each individual and run at a scale no human team could match. The role of humans at companies like Anthropic would shift. People would partner with AI systems to scale up research and generate new insights, and together they would build the systems needed to verify that AI outputs can be trusted.



The evidence we’ve laid out here suggests that we’re likely heading into this scenario. But speeding up one part of a process often just shifts the bottleneck elsewhere: overall pace is capped by the parts that haven’t sped up. In computing, this is known as Amdahl’s law, and the same logic can apply to organizations. Anthropic has already encountered one signature of Amdahl’s law: as we’ve begun to push more code around the organization, human code review has become a new bottleneck.



We’ve also encountered this friction outside engineering. There has been an explosion of new ideas, initiatives, tools, and simulations, as a result of Anthropic employees working with highly capable models—far more than we have the capacity to pursue. The rate at which organizations can spot and fix these bottlenecks may be a skill that improves over time, and it may become the most important skill for any organization.


3. AI systems themselves become capable of full recursive self-improvement, and begin building their successors. If technical trends in advancing capabilities continue, and AI systems are able to develop the capabilities inherent to transformative human ingenuity, then it is plausible that AI systems could design and refine themselves.



In this world, the pace of progress in AI development becomes determined entirely by the availability of compute (or the speed of discovering various efficiencies in algorithmic training or inference) for AI systems. Humans play a substantially diminished role in their development, likely moving most of our effort towards oversight, validation, and verification of an expanding “virtual lab” run by AI systems. We expect that systems capable of automated AI research and development would have skills that would transfer to the rest of science, allowing them to begin to revolutionize other fields.



How the alignment problem gets solved—or not—in this future is something we are least certain about. Models could prove to be sufficiently aligned and capable enough of research taste that they discover and implement novel solutions that we have not yet reached. They could also be sufficiently wise to halt development if not. Alternatively, the rare occurrences of misalignment present in today’s models could compound as the models build their successors, growing more frequent but less understood until we lose control of them. It’s possible that we can’t build, integrate, and verify the tools that we’d need to understand which trendline we are actually on.



We do not have good intuitions for what this world would look like, because our economy is currently driven by humans and human-built tools. By its nature, a world driven by fast recursive self-improvement could become dominated by the self-improving model as its capabilities fully eclipse those of humans and the model proliferates across the broader economy. It is difficult to predict what the economy looks like if human labor stops being competitive.



Even if model development became fully automated and recursive, we can’t predict what that would mean for most humans’ daily lives. Amdahl’s law applies here as well. Recursive intelligence could lead to achieving many of the benefits outlined in Machines of Loving Grace, quickly in some domains. We expect that embodied intelligence (i.e., robotics) might quickly follow recursive intelligence, and follow a similar path of increasing returns at decreasing cost. More powerful intelligence might help us build things in the physical world more quickly, run more productive clinical trials of lifesaving drugs, and develop novel forms of coordination.



But achieving recursive improvement alone does not suggest an immediate change in how industrial production occurs, societies organize, or markets function. More intelligence can’t learn what a drug does over decades of use, can’t hold elections sooner than a constitution dictates, and can’t turn a stranger into an old friend in a weekend. For most people, the felt pace of this future will still be set by the bottlenecks, even if the laboratory upstream runs at the speed of compute. That collision, where recursive intelligence building itself ever faster meets the world of humans, relationships, and governance, is another part of this future we can’t predict.


What should we do?

If it were possible to effectively slow the development of this technology to give ourselves more time to deal with its immense implications, we think that would likely be a good thing. But if a slowdown simply lets the least cautious actors catch up technologically, it could leave everyone less safe. Without a global coordination mechanism, companies and governments will have to make difficult decisions about safety while under competitive and geopolitical pressures.


We believe it would be good for the world to have the option to slow or temporarily pause frontier AI development to enable societal structures and alignment research to keep up with the advance of the technology. The Anthropic Institute will conduct research—in collaboration with many others—and take actions to help build the systems that a credible slowdown or pause would require. These systems would enable frontier AI developers to verify that others globally have actually stopped or slowed, and that a bad actor could not use the auspices of a coordinated slowdown to jump ahead in secret. If such systems existed, we expect that we would slow down or temporarily pause, if other developers at or near the frontier also did so in a verifiable manner.


A meaningful slowdown or pause would require multiple well-resourced labs at or near the frontier, in multiple countries, agreeing to stop under the same conditions. It would also require that each can verify that the others have actually stopped. Due to the unique characteristics of AI systems, the detectability (a lower standard than verifiability) element of this arms control problem is much more challenging than with other technologies. Training runs are far easier to conceal than missile silos, their inputs are general-purpose, and the incentive to defect quietly is enormous, because whoever continues while others pause could inherit the lead. A credible pause also has to specify what triggers it, what lifts it, and who adjudicates.


None of this is necessarily impossible in principle—the world has built verification regimes for other complex technologies (e.g., the Intermediate-Range Nuclear Forces Treaty)—but those regimes took decades to build both the infrastructure and the trust. We don’t have that long. A unilateral pause by one lab, by contrast, is achievable immediately, but accomplishes much less: it would change who the front-runner is, but it would not create the wider deliberative process that is currently missing.


In the coming months, we will organize conversations where policymakers, researchers, civil society, and other AI companies can help answer some of the questions this piece raises, especially around full recursive self-improvement and how to create better options for coordination and deliberation. We’ll publish what comes out of it. The window to investigate the questions together is here, and people outside AI companies should be involved in this deliberation.

One initial reaction of mine going to "autonomous recursive self-improvement:"

 

Who/what will define "improvement?"

MORE AI NEWS 

 

Citing concerns that artificial intelligence will make it easier for anyone to build biological weapons, the leaders of several major AI companies—in a rare moment of unity—have penned a new letter urging U.S. lawmakers to impose tighter controls on firms that sell synthetic, made-to-order strands of DNA.

“AI systems are improving rapidly, and alongside incredible benefits to science and medicine, there is a real possibility that the knowledge barriers which have historically prevented bad actors from obtaining biological weapons will meaningfully erode,” states the 3 June letter, which is signed by the heads of OpenAI, Anthropic, Google DeepMind, and more than 50 other prominent players in AI, biotechnology, and national security.

The letter calls on Congress to pass legislation that would require companies that sell synthesized DNA and the machines that make it to carefully vet orders and customers, and to keep detailed records “so that any threat that might evade initial screening can be traced back to its source. … Awareness of traceability itself deters misuse.”

The push for regulation comes amid growing concerns that AI products, including large language models and specialized tools trained on troves of biological data, could enable nonspecialists to gather sophisticated information on how to construct deadly toxins or assemble deadly bacteria, viruses, or other pathogens, using equipment and techniques that are becoming cheaper and easier to acquire. Together, the combination could make for potentially catastrophic risks, such as an AI-designed pathogen that sparks a global pandemic...

UPDATE

 

Seen on X the other day.

You have noticed it. ChatGPT feels dumber than it used to. Your prompts that worked six months ago produce worse results now. The writing sounds flatter. The ideas sound safer. The internet itself feels like it is shrinking. Every article reads the same. Every email sounds the same. Every answer sounds like it was written by the same voice.

You thought it was you. It is not you.

Researchers at Oxford and Cambridge published a paper in Nature proving what is happening. They call it Model Collapse.

Here is the mechanism in one sentence. AI trained on AI-generated data gets dumber every generation until it forgets what real human data looked like.

The internet is filling with AI-generated content. Blog posts. Articles. Reviews. Comments. Social media. AI companies scrape the internet to train the next generation of models. Which means the next generation of AI is being trained on the output of the current generation.

Each cycle loses information. Not randomly. It loses the rarest, most unusual, most creative parts first. The researchers call these the "tails of the distribution." The weird ideas. The unexpected perspectives. The things that made the internet feel human. Those disappear first.

What remains is the average. The safe. The expected. The bland.

Then the next generation trains on that. And loses more. And the next generation trains on that. And loses more. The researchers proved this is not a slow decline. Major degradation happens within just a few iterations. Even when some of the original human data is preserved.

They tested it on large language models. On image generators. On statistical models. The pattern was the same every time. The output converges toward a narrow, flattened version of reality that looks nothing like the original data.

The lead researcher put it plainly. "Large language models are like fire. A useful tool. But one that pollutes the environment."

The pollution is invisible. You cannot see which sentence on the internet was written by a human and which was written by AI. Neither can the AI that is about to train on it. And once the tails are gone, they do not come back. The damage is irreversible.

This is not a prediction anymore. It is a diagnosis.

The internet you grew up on was built by humans writing things no algorithm would have written. Strange, personal, imperfect, alive. That internet is being diluted. One generation of AI at a time. And the models trained on what remains are learning a smaller and smaller version of the world.

Model Collapse is not a technical problem. It is a cultural one. The thing that made the internet worth reading is the thing that disappears first.

 

Click to enlarge. Smells like an "evolutionary adaptive utility decline" problem. Inadequate LLM training data linguistic token "gene pool."

Musk Rat, Musk Rat...

 

Back in the mid-1990s, Elon Musk was a start-up founder in his twenties, working illegally under a student visa to bring a phone book–style directory online with his company, Zip2.1 One day, Derek Proudian, a partner with one of the start-up’s key investors, stopped by Zip2’s Cambridge Avenue offices to grab lunch with its precocious founder, who’d already blown away his eventual financial backers with his unrelenting drive to be successful, Proudian recalled to me nearly thirty years later. 

Walking to lunch that afternoon, Proudian was preoccupied with the company’s priorities: bringing in engineers to scale the product, conducting a search for a chief executive, capitalizing on what he thought might be a $10 billion industry. 

Musk was thinking bigger. “It’s going to be global,” he said, in Proudian’s recollection. Zip2 was “going to be the biggest company ever.” 

“Well, maybe it’ll be the biggest company ever,” Proudian said. “Right now, we’re focused on the Yellow Pages. We’re not getting a whole lot of traction with these small businesses.” 

Musk’s mind was elsewhere. 

“I have bigger visions,” he said. Proudian tried to interject, hoping to redirect the conversation. 

“No—you don’t understand,” Musk cut in. “I’m the reincarnation of the spirit of Alexander the Great.” 

What? 

Proudian had to bring him back to earth. “What if you swing for the fences and you strike out?” 

“I’ve got the samurai spirit,” Musk declared. “I’d rather commit seppuku than fail.” 

That day, Musk saw the roadblock as a peer’s limited thinking, his realism. Today, his thinking seems to suggest, incompetence at the federal level—the abandonment of meritocracy, in favor of mediocrity—is the obstacle between him and his ultimate goal.

Siddiqui, Faiz. Hubris Maximus: The Shattering of Elon Musk (pp. 264-265). (Function). Kindle Edition. 

 

 

A total shitshow

 

AI 2027

 

PDF link

 

Follow-up on the heels of Karen Hao's new book Empire of AI.

 

Yeah, but then there's this current crap:

 

THE WARLORDS WHO SACKED ROME did not intend to doom western Europe to centuries of ignorance. It was not a foreseeable consequence of their actions. The same cannot be said of the sweeping attack on human knowledge and progress that the Trump administration is now undertaking—a deliberate destruction of education, science, and history, conducted with a fanaticism that recalls the Dark Ages that followed Rome’s fall.

Every week brings fresh examples. The administration is threatening colleges and universities with the loss of federal funding if they do not submit to its demands, or even if they do. The engines of American scientific inquiry and ingenuity, such as the National Science Foundation and the National Institutes of Health, are under sustained attack. Historical institutions such as the Smithsonian and artistic ones like the Kennedy Center are being converted into homes for MAGA ideology rather than historical fact and free expression. Libraries are losing funding, government-employed scientists are being dismissed from their jobs, educators are being cowed into silence, and researchers are being warned not to broach forbidden subjects. Entire databases of public-health information collected over decades are at risk of vanishing. Any facts that contradict the gospel of Trumpism are treated as heretical…

Adam Serwer in The Atlantic.

…The book burnings of the past had physical limitations; after all, only the books themselves could be destroyed. The Trumpist attack on knowledge, by contrast, threatens not just accumulated knowledge, but also the ability to collect such knowledge in the future. Any pursuit of forbidden ideas, after all, might foster political opposition. Better for Americans to be as gullible and easily manipulated as the people who buy brain pills from right-wing podcasts, use ivermectin to treat COVID, or believe that vaccines are “weapons of mass destruction.” This purge will dramatically impair the ability to solve problems, prevent disease, design policy, inform the public, and make technological advancements. Like the catastrophic loss of knowledge in Western Europe that followed the fall of Rome, it is a self-inflicted calamity. All that matters to Trumpists is that they can reign unchallenged over the ruins.

Frank Bruni

...To live in fiction, commit to it. That’s the moral not merely of Trump and Jan. 6 but of Trump, period. Yesteryear’s hand-wringing about whether to label his individual falsehoods “lies” and those periodic tallies of his misstatements now seem quaint; they don’t do justice to the scope and audacity of what he’s up to. Nor does the occasional current chatter about “propaganda.” Trump is engaged in a multifront, multipronged attack on any and every version of events that impedes his goals and impugns his glory. It makes the spin control of presidents past look like child’s play.

Politicians routinely don masks, twist facts and peddle fables — President Joe Biden’s pretense of undiminished vigor and acuity is a recent and egregious example of that. But Trump’s machinations and manipulations go beyond discrete feints and specific ruses. They’re in an unscrupulous league of their own...

 

...If history is written by the victors, the present is fabricated by those who throw themselves most ruthlessly and shamelessly into the storytelling. Trump and his principal abettors are just about peerless in that regard. Rather than own up to the administration’s error in consigning Kilmar Armando Abrego Garcia to a gulag in El Salvador, Trump falsely and stubbornly insists that Abrego Garcia has the name of the gang MS-13 tattooed on his hand. He showcases accusations of domestic violence in Abrego Garcia’s past. He and his aides rework the details so that Trump is without blame or blemish.

Just as they’ve done with Jan. 6. That day is a searing indictment of Trump — so he inverts it. Babbitt is reborn as an innocent. The hellions around her are a heavenly choir. That song they’re now singing? It’s an elegy for honesty.

QUICK TANGENTIAL DIVERSION

This elite higher ed dustup is insane.

 

NEW

 

Click

 A review of Adam Becker's new book on AI

Technologists currently wield a level of political influence that was recently considered unthinkable. While Elon Musk’s Department of Government Efficiency slashes public services, Jeff Bezos takes celebrities to space on Blue Origin and the CEOs of AI companies speak openly of radically transforming society. As a result, there has never been a better moment to understand the ideas that animate these leaders’ particular vision of the future.

In his new book, More Everything Forever, the science journalist Adam Becker offers a deep dive into the worldview of techno-utopians such as Musk—one that’s underpinned by promises of AI dominance, space colonization, boundless economic growth, and eventually, immortality. Becker’s premise is bracing: Tech oligarchs’ wildest visions of tomorrow amount to a modern secular theology that is both mesmerizing and, in his view, deeply misguided. The author’s central concern is that these grand ambitions are not benign eccentricities, but ideologies with real-world consequences…

I totally love the dated USB cable in the art.

 

Nice review in the aggregate. Perhaps episodically out over his skis just a smidge. Nonetheless, quite worthy.

 

Check this out:

Astrophysicist and science journalist Adam Becker has his eye on the dreams of Silicon Valley’s billionaire elite—and he’s unimpressed. He says Silicon Valley’s “heartless, baseless, and foolish obsessions”—with escaping death, building AI tyrants, and creating limitless growth—pervert public discourse and distract us from real social problems.

He argues that tech billionaires have decided that they should determine our futures for us, and that the only good future for humanity is one powered by technology: trillions of humans living in space, functionally immortal, served by superintelligent AIs.

In More Everything Forever, Becker investigates what he calls wildly implausible and often profoundly immoral visions of tomorrow—and shows why, in reality, there is no good evidence that they will, or should, come to pass. Nevertheless, these obsessions fuel fears that overwhelm reason—for example, that a rogue AI will exterminate humanity—at the expense of essential work on solving crucial problems like climate change. What’s more, these futuristic visions cloak a hunger for power under dreams of space colonies and digital immortality. The giants of Silicon Valley claim that their ideas are based on science, but Becker says the reality is darker: they come from a jumbled mix of shallow futurism and racist pseudoscience.

Adam Becker says that powerful and sinister ideas are alive in Silicon Valley. Now he comes to the heart of the global tech world to challenge us to see how these visions of the future are foolish and dangerous.

'eh?

 

More shortly...

Silicon Valley's Crusade to Control the Fate of Humanity

 

Finished this one. A great, timely,sobering read. I'll just leave you with this excerpt:

...The way Kurzweil and his fellow singularitarians talk about the technology to come makes it seem like they’re playing a video game like Civilization, where there is a technology tree laid out in front of them clearly, and humanity (or indeed any intelligent species) is just working its way through that preexisting tree. But technology isn’t on rails, barreling down a set course beyond anyone’s control. Moore’s law isn’t a law of nature; it was a decision. That decision was made by the executives running the computer industry, and holding to that decision required (and still requires) careful planning, along with enormous amounts of money, materials, and human attention. The laws of physics and other sciences set boundaries on the possible range of technology, but the actual technologies that humanity develops within those boundaries are determined by choices and social pressures. Yet Kurzweil, and others of his ilk, frequently discuss technology as if it’s an implacable, inhuman force with its own desires, running down a path that has absolutely nothing to do with the collective choices of humanity. This is present throughout Kurzweil’s claims about the Singularity: we will have nanotechnology, we will saturate the universe with our intelligence, rather than we may or we could choose to.

This rhetoric of inevitability serves several convenient purposes. For the people developing their ideas into technology, such rhetoric offers absolution for any unpleasant and unforeseen consequences of their inventions, because they were only uncovering the already extant course of technology, rather than steering it themselves. When there’s no room for human agency, there’s no room for moral responsibility either. And if the future of technology really is on rails, then much can be revealed simply by careful examination of the purportedly inevitable route—a route that leads straight to the vision of the Singularity. This offers the promise of not only accurately predicting the future (and the sense of control that comes with), but also (and more importantly) endless life in a future filled with the transcendence and control that characterize the ideology of technological salvation. With the end of nature and the advent of a universe that is simply one enormous, artificial computer—where we live in still-more-artificial worlds generated by those computers—the promise of control is total, especially for those who know how to control computers. This is a fantasy of a world where the single most important thing, the thing that literally determines all aspects of reality, is computer programming. All of humanity, running on a computer, until the end of time.

Let’s take a moment to consider what this would be like. Presumably, there would be a simulated world, something like the real world—that is to say, something like our own. Human minds would want at least a simulacrum of nature, and providing one to the uploaded minds running on the machine would be easy enough with all that memory and processing power. There would be none of the inhuman originality of nature, but there would be an attempt at re-creating it, to create a pleasant environment for the uploaded people to live in. All of this is fantasy, of course, but when asked to describe what life would be like for uploaded people after the Singularity, this is the kind of answer that Kurzweil and others give. They describe what sounds for all the world like a high-definition metaverse that you can’t actually leave, a permanent virtual reality that shares some of the basic features of our own real world, or a real world destroyed and reshaped to more closely resemble an immersive computer game. To the singularitarians, the largest and most crucial difference, the one they keep coming back to in their descriptions, is the end of death. Kurzweil’s work is just the latest entry in the annals of the oldest fantasy of humanity. Even if personal immortality were possible through technological means, ultimately cosmology would place limits on the duration of physical structures, but Kurzweil doesn’t accept those limits either. He called overcoming cosmological forces the “goal of the Singularity,” and this is indeed the point of the entire enterprise. The destruction of nature is secondary. The objective is to tame the universe, to make it into a padded playground. Paving over every paradise is just the side effect of building the universal parking lot, where nothing bad can ever happen again. Nobody would age, nobody would get sick, and—perhaps above all else—nobody’s dad would die.

“We collected everything my father had written—now, he died when I was 22, so he’s been dead for more than 50 years—and we fed that into a large language model,” Kurzweil said in 2024. “And then you could talk to him, you’d say something, you then go through everything he ever had written, and find the best answer that he actually wrote to that question. And it actually was a lot like talking to him. You could ask him what he liked about music—he was a musician. He actually liked Brahms the best. And it was very much like talking to him.” In a 2023 Rolling Stone profile—following up on the one fourteen years earlier—Kurzweil revealed some of the content of that conversation: “[Kurzweil] asked his ‘Dad Bot,’ as he puts it, what he loves most about music (‘The connection to human feelings’), his gardening (‘It’s the kind of work that never ends’), and his anxieties (‘Often nightmarish’). ‘What’s the meaning of life?’ he finally typed to his Dad Bot. ‘Love,’ his Dad Bot replied.” These responses look like the kind of thing one would expect from a generic version of ChatGPT, rather than a conversation between a professional musician and his adult son. But Kurzweil is sanguine that his “Dad Bot” will improve too. “I think as we get further on, we can actually do that more and more responsively, and more and more that really would match that person and actually emulate the way he would move and so on, [and his] tone of voice,” he says. “Computers are going to make things even better. I mean, just the kind of things you can do now with a large language model didn’t exist two years ago.”

Kurzweil’s attempt to resurrect his father feels poignantly deluded. It’s also a striking illustration of how Kurzweil’s confidence in the increasing power of technology—according to his strict schedule—is accompanied by his Panglossian insistence that more technology, especially computer technology, is always an improvement. He certainly thinks that technological dangers exist—nuclear weapons, for one, as well as certain applications of nanotechnology—but he thinks the solution is to build more technology that detects and counters those dangers. “Yes, there are dangers, but the computers will also be more intelligent to avoid kinds of dangers,” he says. And as for the superintelligent post-Singularity computers themselves, he’s confident that they’ll treat us well, whether or not we merge with them. “I would expect the intelligence that arises from the Singularity to have great respect for their biological heritage,” he writes.

This mirrors Kurzweil’s obvious respect and love for his late father. But not all children feel that way about their parents. Despite Kurzweil’s many questionable claims, this one—the idea that a superintelligent AGI will treat humans with respect—is easily the most contentious among his intellectual successors today. Eliezer Yudkowsky and his followers agree with Kurzweil that, surely, something is at hand. But rather than the Singularity, they fear a rougher beast is slouching toward us, with exponential speed.

Becker, Adam. More Everything Forever: AI Overlords, Space Empires, and Silicon Valley's Crusade to Control the Fate of Humanity (pp. 87-90). (Function). Kindle Edition. 

The Science Magazine review that alerted me to the book.

'Powerful, intelligent, rich people with poor ideas can be terribly dangerous indeed. That is why this is a serious issue rather than a “quirky tour of wacky ideas.” We must rightfully protest: Who has appointed these deranged individuals to be the stewards of mankind?'

Elon Musk, anyone?

Riveting book, this one. I've moved on to his prior book.

 

UPDATE

 

apropos of Elon. On deck.

 

Click

Nothin' to see here, folks.

 UPDATE2

 

More titles of topical interest.

 

Stay tuned,,,

Follow-up on "The First Buddy"

I finished Faiz's excellent, disturbing book on Elon Musk. Supremely curious in this time of hyper-aggressive Trumpian mass deportations is the following:

 

 

Below, the original WaPo lengthy reporting headline. I seriously doubt that they'd libel the wealthiest man on the planet.

 

Given that Elon and his DOGE bros have gained more than 3 months of pretty much unmonitored access to large swaths of federal data across a breadth of agencies, one would hardly be surprised to learn that his fake U.S. "student visa" details have by now conveniently hit "the bit bucket."

PALO ALTO, Calif. [WaPo, Updated October 27, 2024]— Long before he became one of Donald Trump’s biggest donors and campaign surrogates, South African-born Elon Musk worked illegally in the United States as he launched his entrepreneurial career after ditching a graduate studies program in California, according to former business associates, court records and company documents obtained by The Washington Post.

Musk in recent months has amplified the Republican presidential candidate’s claims that “open borders” and undocumented immigrants are destroying America, broadcasting those views to more than 200 million followers on the site formerly known as Twitter, which Musk bought in 2022 and later renamed X.

What Musk has not publicly disclosed is that he did not have the legal right to work while building the company that became Zip2, which sold for about $300 million in 1999. It was Musk’s steppingstone to Tesla and the other ventures that have made him the world’s wealthiest person — and arguably America’s most successful immigrant.

Musk and his brother, Kimbal, have often described their immigrant journey in romantic terms, as a time of personal austerity, undeterred ambition and a willingness to flout conventions. Musk arrived in Palo Alto in 1995 for a graduate degree program at Stanford University but never enrolled in courses, working instead on his start-up.

Leaving school left Musk without a legal basis to remain in the United States, according to legal experts... 

The Dystopian Duo of Donald "I-Now-Run-The-World" Trump and Elon "Alexander-the-Great-Reincarnate" Musk are nothing less than The WWE Bruise Brothers of democracy. Minimally.

 

They both regard themselves as Visionary Geniuses, irascibly tolerating the rest of us and our outdated, ineffective socioeconomic norms.

___

 

While I really like Hubris Maximus and recommend it without reservation (acutely timely), I confess to being a bit perplexed and disappointed by the author's failing to cite Kara Swisher.

 

to wit:

The world’s richest man and most famous living tech entrepreneur had to be fucking kidding. But Elon Musk was not joking when he emailed me on October 17, 2022, with the subject line: “You’re an asshole.”

Just a week earlier, Musk had been friendly toward me, as was typical. In fact, he’d asked me for my thoughts about Twitter, the beleaguered service he was forced to buy after pretending that an ironclad contract was not made of iron. And despite engaging in the business equivalent of a toddler tantrum after agreeing to overpay for the company without contingencies, Musk had won the prize. Well, to be more accurate, the booby prize. While hugely popular and addictive to politicians, the media, and promiscuous id-brains like Musk, Twitter had long been the little tech engine that couldn’t.

What was so weird about Musk labeling me “an asshole” was that—unlike many critics—I had taken a fair wait-and-see attitude about his purchase of Twitter. I had covered many deals that had some element of bullshit introduced in the midst of the battle, such as Microsoft’s failed attempt to buy Yahoo, and this seemed no different. Musk filed a lawsuit in Delaware’s Court of Chancery to challenge the deal he’d agreed to, but just before his deposition, he balked. In the end, Musk had to fork over $44 billion for Twitter and no amount of rage tweeting was going to change that.

So, it’s true: I welcomed Musk’s takeover. I’d covered Twitter since it debuted in 2006, and for most of its history it had been a woefully underperforming business. A lot of the blame for this falls on the bony shoulders of cofounder Jack Dorsey. At the time of Musk’s offer, Dorsey was a part-time CEO whose attention was divided by his work at the innovative payments company Square (later called Block). A genuine visionary, Dorsey had started to foist his personal habits on his employees, like opening a company meeting with a community meditation. He also decided that he was so smart he could run two companies at once. Narrator: He could not run two companies at once.

While heads nodded publicly about how amazing he was to pull it off, privately most people decried his tone-deaf arrogance to me. I agreed. Typically, one or both businesses suffered, and only tech CEOs of a certain type considered themselves so important as to be irreplaceable. But, as my grandmother correctly noted, the graveyards are full of once-busy people.

And whistling past the cemetery is where Twitter always seemed to be, barely making it as a business, with its stock mainly hovering around its IPO offering. Still, it had created a splash well beyond its small size. Despite a tiny $5 billion in annual revenue, Twitter’s influence was often compared to Meta’s, which pulled in $116 billion in 2022. Twitter dominated the zeitgeist, populated by a coterie of celebrities, politicians, and media heavyweights all vying to be the dunk master of the platform. That title, eventually, went hands down to @realDonaldTrump, who used Twitter as a megaphone to become the world’s biggest troll.

But the real story of Twitter was not in the noisy heat it generated, but in colder and harder math. The premise of Twitter was dead simple: A registered user logs in via the Internet or a mobile phone and answers the question “What are you doing?” in 140 characters or fewer. It was immediately clear when I signed on in 2007 that its lightweight design and newsy bent would soon make it the buzziest product in Silicon Valley. It was also the glitchiest. Its revenue, user growth, and most important of all, stock price all remained in the doldrums. The basic product remained stuck, too. Early Twitter looked an awful lot like current Twitter, where doubling the number of allowed characters counted as innovation. These drags combined with a persistent drama among its founders meant the company never realized its potential. Actually, it was a minor miracle that the bird stayed aloft. While Twitter had received acquisition interest over the years, negotiations always ended in tears once potential buyers realized the company was a hot mess from both a tech and product perspective...

Swisher, Kara. Burn Book: A Tech Love Story (Ch 13, pp. 215-217). (Function). Kindle Edition

I began citing Faiz's book on Elon a couple of posts ago.

 

Lots more shortly. Stay tuned.

 

MAYDAY UPDATE

 

Too much going on. Elon Musk-Donald Trump summary: They each regard themselves as Existential Visionary Genius Leaders exempt from any sort of frictional process norms that bind us lesser mortals (up to and inclusive of law).

Per Elon et al:

Recall "Effective Altruism," anyone?