Ah, Elon Musk, that Mars-obsessed billionaire who can’t seem to resist making more money. Recently reclaiming the crown as the world’s richest person, thanks to Tesla shares soaring like one of his SpaceX rockets. Yet, what sets him apart from the billionaire boys club is not just his penchant for colonizing other planets or launching cars into space but what he doesn’t do with his money. While other moguls might splurge on ostentatious yachts or golden toilets, Musk opts for robots, rockets, and cyborgs.
Musk is not just content to sit back and enjoy his wealth in earthly delights. Instead, he’s got his eyes firmly set on another payday. This time it’s from Starlink, SpaceX’s satellite-broadband branch, poised for a potential spinoff and IPO. According to Chamath Palihapitiya, the venture capitalist with a crystal ball, we should expect this financial extravaganza within the year, potentially rocketing Musk’s fortune to new stratospheric heights.
Earlier this month, the Wall Street Journal was abuzz with news of SpaceX’s attempts to boost its valuation to a cool $150 billion. This plan seems to involve letting employees sell stock, a move as unconventional as the man himself. Musk, ever the maverick, is not just dabbling in space travel, but also space economics.
When asked about the potential Starlink IPO, Musk responded with a classic Muskian quip: “It would not be legal for me to speculate about a Starlink IPO,” followed by laughter. His chuckle carried an undeniable hint of irony. After all, when has legal speculation ever been a deterrent for a man planning to colonize Mars?
So, as Musk’s wealth continues to expand like the universe he’s so keen to explore, we can find solace in one thing: that added wealth probably won’t end up invested in luxury yachts or extravagant parties. Instead, it will be funneled into his vast array of futuristic projects. After all, why buy a yacht when you can invest in building a spaceship?
So let’s raise a glass (or a spacesuit helmet) to Musk. Here’s to hoping that the increase in his fortune propels us all into a future filled with cool technology, courtesy of the eccentric billionaire who prefers rockets to yachts.
In the realm of fame and success, there exists a tipping point where the brilliance of an individual’s achievements converges with the potential for peril within the context of their influence. Elon Musk, a figure of immense acclaim, adulation, and controversy, may have tipped over this point. His innovative prowess and entrepreneurial triumphs have garnered widespread admiration, yet his power could become a perilous force.
Musk’s dominion extends beyond the realm of technology. His ventures stretch into the realms of space exploration, renewable energy, and even neural interfaces. As his empire expands, so does his sway over the public imagination. However, the question lingers: When does this power become precarious?
Elon bought Twitter, famously overpaying for it. He likes to joke that he couldn’t be that smart since he overpaid for it. Which, is a great joke, but misses the point: Money isn’t a problem at this stage of Musk’s story. Price doesn’t matter; Position is what matters. This is what we mean by a loss leader in business-speak. Remember that Microsoft gives away software that is in any category that they want to control. And with Twitter, Musk is at least a decade ahead in building an “everything” app. Imagine an app that ties together news, social connections, gaming, content, asset trading, and personal finance. It’s the CCCP in your palm.
The allure of Musk’s success can lead to an aura of infallibility. The potent cocktail of both his colossal achievements and his devout following may actually deceive as what is possible. However, he is combining different things that usually aren’t combined: Amazing business achievement and blind idolatry; power, money, and worship.
Moreover, Musk’s penchant for audacity and provocation stirs a tempestuous cauldron of public opinion. While some applaud his unorthodox methods and unyielding determination, others view his behavior as recklessness veiled by a charismatic persona. The risk arises when the magnetism of his narrative overshadows the underlying ramifications of his decisions.
A parallel can be drawn to another polarizing figure: Donald Trump. His divisive rhetoric and strategic storytelling captivated a devoted following. By weaving a tale that resonated with their desires and fears, he fashioned an unwavering cult-like allegiance. But let’s be honest, Trump is much more talented at imagining his accomplishments than he is accomplishing anything. For example, he had both houses of Congress and did nothing legislatively. Imagine someone with the competence of Musk and the ability to both sense the narrative people want to hear and the ability to spin those threads in their minds. Imagine a brew of colossal competence and the Big Lie.
Ultimately, the juncture where fame and success morph into peril necessitates a vigilant society. It calls for a discerning populace capable of both celebrating remarkable accomplishments and questioning the ramifications thereof. The onus lies not only on the individual but also on the collective to strike a harmonious balance, embracing innovation while safeguarding against the encroachment of hubris. Only through such equilibrium can the risks inherent in the dynamics of power be mitigated, ensuring a healthier, more introspective society.
Elon Musk, the renowned entrepreneur and visionary, stated that we are on the event horizon of the black hole of AI. This quote encapsulates the deep uncertainty surrounding the future of Artificial Intelligence (AI) and specifically, the future development of Artificial General Intelligence (AGI).
AGI usually refers to AI systems that possess human-like intelligence and abilities across a wide range of tasks. There is a better way to wrestle with this issue. What do we do when machines seem to have souls?
While AGI holds immense potential to revolutionize our world, it also brings about unprecedented challenges and risks. Musk’s analogy to a black hole’s event horizon emphasizes the critical juncture we find ourselves in – a point of no return where the consequences of our actions become increasingly uncertain.
The largest cost of learning has long been a significant barrier to knowledge and its subsequent offspring, including productivity and wealth. While the animal kingdom possesses a form of learning through behavior, the cost is existence itself. This is why death is the adaptation; the driver of change. Humanity’s distinctive advantage lies in our ability to learn through language. However, this form of learning is not without its limitations. Think years and years of school. Now, consider a scenario where programmable learning becomes available instantaneously available with virtually zero cost at the margin. The implications of such a breakthrough are staggering. With the removal of the “costs” of acquiring knowledge, entities would have the unprecedented ability to continuously expand their intellectual horizons. In fact, the “horizon” of their knowledge becomes the only learning they can gain; because the cost of learning some other knowledge is simply a download. How do we describe a world like this? Answer: We don’t!
It’s the singularity. The black hole.
Our major concern becomes the loss of control. As machines surpass human capabilities and their goals cease to align with ours, perhaps we will have created the deity that we wish for: A Nanny on high who won’t allow tragedies or suffering. Perhaps we will trade autonomy for security.
Despite these concerns, it is important to acknowledge the tremendous potential AI and AGI hold for positive change. From advancements in healthcare and scientific research to enhancing transportation systems and mitigating climate change, these technologies can contribute to a better future.
As we stand on the precipice of this black hole of AI, it is crucial that we approach its development with a balanced perspective. We must strive for transparency, robust regulation, and proactive collaboration among industry leaders, policymakers, and the public. By doing so, we can navigate the uncertain terrain of AI and AGI and shape a future that maximizes their benefits while minimizing their risks.
The emergence of groundbreaking technologies has consistently fueled narratives of bubbles throughout history. From electricity to oil, railroads to the internet, and social media to software, each innovation has sparked a surge in speculation and investment. However, in our generation, the largest bubble narrative is undeniably centered around artificial intelligence (AI) and its various offshoots. While some may be cautious and opt to avoid this perceived bubble, I firmly believe in embracing it and seizing the opportunities it presents.
To navigate the AI bubble successfully, one can employ sophisticated algorithms designed to monitor the market’s health. These advanced tools can analyze patterns, trends, and indicators, providing valuable insights into investment decisions. By leveraging these algorithms, one can make informed choices and capitalize on the bubble’s potential.
But what if you don’t have access to such sophisticated algorithms? Even then, there are simpler strategies that can be effective. For instance, utilizing a 50-day simple moving average can be an accessible yet powerful tool. This technique involves calculating the average price of an asset over the past 50 days and using it as a reference point for buying or selling decisions. By following this moving average, investors can capture a significant portion of the bubble opportunity.
In conclusion, the AI bubble narrative represents a significant moment in our generation. Instead of shying away from it, I advocate embracing the potential it holds. With the aid of sophisticated algorithms or even simple strategies like the 50-day moving average, investors can position themselves to ride the wave of this technological phenomenon and reap the benefits it offers.
The integration of Artificial Intelligence (AI) into the global economy holds immense promise, heralding a new era of technological progress and productivity. However, it also presents considerable challenges. Let’s put into three words: Disruption, data, and doom. Or more properly: employment disruption, data privacy, and AI ethics.
Firstly, employment disruption tops the list of challenges. AI’s ability to automate tasks could lead to significant job displacement across several sectors, particularly in jobs involving routine tasks. While new jobs may emerge from the AI revolution, there is a growing concern about the ‘skills mismatch.’ Workers displaced from one industry may find it difficult to transition into new roles without significant reskilling and upskilling. Thus, ensuring smooth workforce transition is a pressing issue.
Secondly, data privacy is a serious concern. AI systems thrive on massive data sets, some of which may contain sensitive personal information. The collection, storage, and processing of such data pose substantial privacy risks, especially with the increasing sophistication of AI in data analysis. Regulations must evolve to protect privacy and define clear boundaries for data usage in AI applications.
Lastly, the ethical implications of AI pose a complex challenge. AI decision-making can reflect the biases in the data it was trained on, leading to potential discrimination or unfair outcomes. Moreover, decisions made by AI systems are often ‘black-box’ processes, lacking transparency, which makes it difficult to hold them accountable. Establishing ethical standards and frameworks for AI use, developing interpretable and transparent AI models, and continuously auditing AI systems will be vital. If AI is a future threat to humanity, it will first fail in ethics.
In conclusion, the integration of AI into our future economy presents a transformative opportunity that is probably the most complex thing humanity has ever done.
That rapid improvement has led to what’s being called “Neven’s law,” a new kind of rule to describe how quickly quantum computers are gaining on classical ones. The rule began as an in-house observation before Neven mentioned it in May at the Google Quantum Spring Symposium. There, he said that quantum computers are gaining computational power relative to classical ones at a “doubly exponential” rate — a staggeringly fast clip.
With double exponential growth, “it looks like nothing is happening, nothing is happening, and then whoops, suddenly you’re in a different world,” Neven said. “That’s what we’re experiencing here.”
Technology that harnesses brain activity to produce synthesised speech may benefit individuals who have been robbed of the ability to talk due to a stroke or other medical conditions, researchers claim.
Known as a ‘brain decoder’, the technology is said to read people’s minds and turn thoughts into speech – a tool which could one day help doctors communicate with patients who cannot talk.
Scientists at the University of California, San Francisco (UCSF) implanted electrodes into the brain of volunteers and then decoded signals in cerebral speech centres to guide a computer-simulated version of their vocal tract – lips, jaw, tongue and larynx – to generate speech through a synthesiser.
The results from the volunteers were mostly intelligible, although the researchers have noted that the speech is somewhat slurred in parts.
“We were shocked when we first heard the results – we couldn’t believe our ears,” said UCSF doctoral student Josh Chartier. “I was incredibly exciting that a lot of aspects of real speech were present in the output from the synthesiser.”
Results from the study have raised hope among the researchers that, with improvements, a clinically viable device could be developed for patients with speech loss in the years to come.
“Clearly, there is more work to get this to be more natural and intelligible,” Chartier added, “but we were very impressed by how much can be decoded from brain activity.”
A stroke, ailments such as cerebral palsy, amyotrophic lateral sclerosis (ALS), Parkinson’s disease and multiple sclerosis, brain injuries and cancer sometimes take away a person’s ability to speak.
Such conditions result in some people using devices that track eye or residual facial muscle movements to spell out words letter-by-letter. These methods, however, are slow, delivering typically no more than 10 words per minute in comparison to 100-150 words per minute in natural speech.
The five volunteers who took part in the study were all epilepsy patients. Although they were all capable of speaking, they were given the opportunity to participate as they were already scheduled to have electrodes temporarily implanted in their brains to map the source of their seizures before neurosurgery. Future studies will test the technology on people who are unable to speak.
The volunteers read aloud while activity in brain regions involved in language production was tracked. The researchers discerned the vocal tract movements needed to produce the speech and created a “virtual vocal tract” for each participant that could be controlled by their brain activity and produce synthesised speech.
“Very few of us have any real idea, actually, of what’s going on in our mouth when we speak,” said neurosurgeon Edward Chang. “The brain translates those thoughts of what you want to say into movements of the vocal tract, and that’s what we’re trying to decode.”
The researchers found that during the study, they were more successful in synthesising slower speech sounds such as “sh” and less successful with the abrupt sounds such as “b” and “p”.
Furthermore, the technology did not work as well when the researchers tried to decode the brain activity directly into speech, without using a virtual vocal tract.
“We are still working on making the synthesised speech crisper and less slurred,” Chartier said. “This is in part a consequence of the algorithms we are using, and we think we should be able to get better results as we improve the technology.”
“We hope that these findings give hope to people with conditions that prevent them from expressing themselves that one day we will be able to restore the ability to communicate, which is such a fundamental part of who we are as humans,” he added.
The study has been published in the journal Nature.
To be fair, Elon isn’t a problem to be solved. He is just doing what he does –geeking out, innovating, living life. But as a fan of innovators and a student of markets, I can’t help but try to understand the motives of Mr. Musk. (Full disclosure: I’m a Elon Musk fan)
So, to speak presumptively, Elon probably has something close to a technological messiah complex. This isn’t bad, quite the contrary. We need brilliant people to care about the future. I agree with Tim Urban’s take on Elon. I’ll summarize: Start with a good outcome for humanity and work backwards. Why do I bring this up? Okay, I’ll jump to the big question:
Why did Elon buy Solar City?
Buying Solar City wrecked the balance sheet of Tesla, and placed the company in a much more difficult place. Of all the companies that Elon is involved in Solar City is the only one with no obvious technological edge. In fact, if Tesla wanted to be a one-stop-shop for all things carbon-free it would make more sense to simply partner/license the solar tech. Why buy Solar City?
The solar-tile? Me thinks not. Not enough innovation there.
To bail out cousins? Surely not, there are much more efficient ways to help family than to take over a struggling company.
To facilitate collaborative engineering between Tesla and Solar City? Maybe. This is supposed to be the year of solar-tile and the power-wall. But buying the company was unnecessary. Just do a deal with Solar City, but develop the power-wall as compatible with all solar units. Be Microsoft not Apple. And don’t take over a bunch of debt.
I believe that Mr. Musk was somehow thinking as a technological messiah, not a capitalist, when he did the Solar City deal. Now his shareholders are paying the price, and the risk-of-ruin for Tesla is substantially higher.
Whatever the case, this is the year where Solar City either makes sense, or doesn’t.
Part of this blog’s goal is to show our actual numbers in a more accountable way. Here are the signals sent by our current US market algo. These signals are drawn from meta-data derived from the whole market. Currently, we are struggling to find trade-able meta-data for any one stock. We have had some success looking for that data in sectors (and we may post a riskboard for sectors in the future.) However, the meta-data for whole markets is excellent.
Our minds do not grasp non-linear math, not easily anyway. This is why young people don’t save money and why older people shrug off technological change. This is the best illustration I have seen on this subject.
This understanding applies directly to our world, both socially, scientifically, and financially. The folks over at Ark Invest gives us this list (their work is fantastic).
1. Deep Learning –
Is it a larger opportunity than the Internet?
2. Digital Wallets –
Could they spell the end of traditional banks?
3. Cryptocurrencies –
Are we witnessing the rise of an alternative financial system?
4. Battery Cost Tipping Point –
Could EVs become cheaper than comparable gas-powered cars?
5. Autonomous Taxi Networks –
Will they become the most valuable investment opportunity in public equity markets?
6. Next Generation DNA Sequencing –
Could it unlock the code to life, disease, and death?
7. CRISPR For Human Therapeutics –
Will health care become cheaper and curative?
8. Collaborative Robots –
Will robots be your next co-worker?
9. 3D Printing for End-Use Parts –
Will manufacturing ever be the same?