WHY THIS MATTERS IN BRIEF

Elon Musk has a beef with Sam Altman and OpenAI, and now he wants to buy the company … or does he just want to slow them down enough to catch them?

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As if Elon Musk doesn’t have enough going on, a consortium of investors led by him announced plans Monday for what appears to be a hostile takeover of OpenAI. The investor group offered nearly $97.4 billion – which would make it one of the biggest M&A deals in history – to buy all of OpenAI’s assets and is “prepared to consider matching or exceeding higher bids,” it said in a press release sent to reporters.

OpenAI CEO Sam Altman isn’t having it. He immediately replied on X, “no thank you but we will buy twitter for $9.74 billion if you want,” and said that Musk was simply “trying to slow OpenAI down.”

The consortium includes Baron Capital Group, Valor Management, Atreides Management, Vy Fund III, Emmanuel Capital Management, and Eight Partners. While Emanuel Capital Management has a slimmer public profile, the others are firmly in Musk’s orbit.

Baron Capital Group, which manages multiple mutual funds, was founded by Ron Baron. The firm’s Baron Partners Fund, which he manages with his son Michael Baron, has large stakes in Tesla and SpaceX.

Atreides Management is associated with Boston-based hedge fund Atreides. As we previously reported, founder Gavin Baker spent 18 years at Fidelity where he made his first investment in SpaceX. Atreides has also invested in Tesla and Baker was a public supporter of Musk’s enormous Tesla pay package.

Valor Management was founded by Antonio Gracias, an early SpaceX investor and former Tesla board member. He was also an investor in Musk’s SolarCity before Tesla acquired it.

Vy Capital, founded by Alexander Tamas, also has a SpaceX stake and has invested in a number of other Musk companies like The Boring Company and Neuralink.

Eight Partners VC is better known as Joe Lonsdale’s firm 8VC, according to public filings. Lonsdale is a vocal fan of Musk and runs in similar circles. He recently appeared on CNBC calling himself “a huge fan” of Musk’s DOGE, an interview that Musk reposted on X.

It’s not yet clear how serious this group is. One plausible analysis floating around the internet is that this is as much trolling as offer. Some say this is Musk’s attempt to drive up the price that Altman’s team would have to pay to buy OpenAI’s underlying assets in order to restructure it from its original non-profit status.

Musk was part of the founding of OpenAI as a nonprofit AI research organization and Musk has been attempting to halt Altman’s restructuring plans.

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The human brain can multi-task and react and respond faster to threats than the human body, so now the US military is taking the body out of the loop.

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In past experiments small mini brains known as organoids, which are now being trained on Dopamine to improve them, have out performed some pretty impressive Artificial Intelligences (AI) which means that when it comes to beating AI powered combat drones and advanced wingmen being able to tap into the human brain might provide an advantage.

Military pilots fighting an enemy need to engage in complex manoeuvres that take precious seconds or minutes of their time and attention. Advanced touch screens or voice commands allow them to perform those actions faster, but it still can take precious seconds. That time could mean the difference between life and death.

US military researchers have a solution in mind, literally – a high-tech helmet that connects directly to the pilot’s brain without requiring surgical implants, enabling two-way brain-to-computer communication. This helmet would interpret brain waves and carry out multiple functions in nanoseconds. Theoretically, it would let pilots carry out sophisticated tasks, such as directing drones into combat remotely, through the power of thought alone. Or pilots could transmit what they see to a military base and receive information back through the helmet to their brains.

The type of non-invasive neurotechnology being developed might also enhance a brain’s ability to recall key information, learn new skills faster, and even perform difficult tasks with assistance from a remote specialist.

In 2018 DARPA began a $125 million program called Next-Generation Non-surgical Neurotechnology (N3), which was aimed at accomplishing precisely that. In theory, the N3 helmet would create a pathway to integrate cybernetics into the military without having to insert devices into human bodies.

“By creating a more accessible Brain Machine Interface (BMI) that doesn’t require surgery to use, DARPA could deliver tools that allow mission commanders to remain meaningfully involved in dynamic operations that unfold at rapid speed,” Al Emondi, the N3 program manager, said in a DARPA press release.

Via 16 independent channels interacting with different parts of the brain, this helmet is intended both to sense output from the wearer’s brain and to transmit data to that brain using some combination of magnetic, optical and acoustic neural transmitters. Program documents also state a requirement to interact with 16 cubic millimeters of neural tissue within 50 milliseconds.

While the final product is still possibly years away, DARPA has been working on neural projects like this one for decades, pouring more than $1 billion into neuroscience since 1973. Following a renewed influx of funding post-1999, DARPA research has resulted in multiple breakthroughs, starting with experiments in the 2000s in which monkeys proved capable of moving a cursor on a computer screen – and then an artificial arm – through thought alone. In the next significant experiment, humans performed more complex, thought-directed tasks such as piloting ground and air vehicles, including a simulated F-35 stealth fighter.

Despite these advances, DARPA’s work hasn’t produced systems intended for operational use – yet. There are several major obstacles. One is that most prior research depended on implants to establish a direct link to the brain. For now, the military seems intent on focusing on communication systems that don’t require implants, the sort Elon Musk is testing with Neuralink.

Over the past decade DARPA funded researchers have made several inroads toward the brain-helmet interface goal. A Johns Hopkins University Applied Physics Laboratory team aims to develop a “completely non-invasive, coherent optical system for recording from the brain,” according to DARPA page announcing the research. The system would measure optical changes in neural tissue that correlate with neural activity. Meanwhile, a Palo Alto Research Center team in California plans to pair ultrasounds and magnetic fields to create localized electrical currents that could transmit data to the brain, according to the DARPA press release. A third team, at Teledyne in Thousand Oaks, California, is using magnetometers to detect brain activity via magnetic fields, and ultrasound to transmit those signals to neurons. A fourth team at Carnegie Mellon also plans to use ultrasound, paired with pulses of skull-penetrating light to read brain activity, as well as manipulation of magnetic fields to write to brains.

Other methods for N3 aren’t truly non-invasive, but rather minutely invasive. For example, a team at the neurotechnology company Battelle based in Columbus, Ohio, is researching the non-surgical insertion of nanotransducers, tiny devices to convert the brain’s electrical signals into a format that an external transceiver can read. The devices aim to work in reverse too, for full transmit-and-receive connectivity.

Meanwhile, a group at the University of Technology Sydney, in Australia, announced in 2023 that they had developed a non-invasive device using a graphene sensor to monitor brain visualization, enabling mind-control of a robot dog based on a menu of nine possible commands.

What if we make the leap to sending and receiving data between brains: a Brain-to-Computer-to-Brain link though? That too may be possible, with N3’s MOANA program. Short for “Magnetic, Optical and Acoustic Neural Access,” MOANA aims to enable direct Brain-to-Brain communication. Researchers at Rice University in Houston, Texas injected gene-therapy payloads to essentially reprogram neurons to be more receptive to “write” capability using magnetic field manipulation. At the same time, the researchers used skull-penetrating light to fulfil the read functions.

Such capability could one day be harnessed to allow a remote specialist to assist a non-expert in performing specific actions – like providing emergency medical care or repairing a complex device. That sounds farfetched, but researchers at Wake Forest University, the University of California, and the University of Kentucky established a neural-link between rats in 2009. The experiment enabled an inexperienced rat to perform a task in minutes that an experienced rat required weeks to learn.

At least one major new military platform on the horizon is planned to integrate ‘read’ capability: the Tempest sixth-generation jet fighter that the UK, Japan, and Italy are developing should include a flight helmet that monitors the pilot’s brain activity and other biometric data including skin response, heart rate, respiration, eye tracking, and EKG. Onboard AI could one day use this monitoring capability to decide whether to step in should the pilot need emergency assistance.

So far, none of these projects have led to technology that is ready for the military to use. DARPA has not yet released the results of these avenues of research, but it’s clear there’s still a great deal of work ahead.

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WHY THIS MATTERS IN BRIEF

Changing how you define something affects how you develop it and measure it, as well as it’s utility. By having a financial definition of AGI many humanity centric benefits may be lost.

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OpenAI and Microsoft have a secret definition for “AGI,” an acronym for Artificial General Intelligence or any system that can outperform humans at most tasks – which was the original loose OpenAI definition of AGI. Recently, I’ve been talking about how Google DeepMind and OpenAI suggested that a new Turning Test for Artificial Intelligence (AI) should be based on an AI’s ability to build, run, and scale a highly profitable business – as well as build multi-billion dollar businesses which it’s on track to do. So, perhaps the new definition, which is a commercial definition of AGI, shouldn’t come as much of a surprise.

According to leaked documents obtained by The Information, the two companies came to agree in 2023 that AGI will be achieved once OpenAI has developed an AI system that can generate at least $100 billion in profits – presumably by itself. And not only would this be a staggering feat making a new era of AI, but it would also have significant ramifications for the global economy – something else I’ve talked about recently as well but from a completely alternative angle.

The Future of Artificial Intelligence 2030, by Keynote Speaker Matthew Griffin

There has long been a debate in the AI community about what AGI means, or whether computers will ever be good enough to outperform humans at most tasks and subsequently wipe out major swaths of the economy.

The term “artificial intelligence” is something of a misnomer because much of it is just a prediction machine, taking in keywords and searching large amounts of data without really understanding the underlying concepts. But OpenAI has received more than $13 billion in funding from Microsoft over the years, and that money has come with a strange contractual agreement that the startup would stop allowing Microsoft to use any new technology it develops after AGI is achieved.

OpenAI was founded as a non-profit under the guise that it would use its influence to create products that benefit all of humanity. The idea behind cutting off Microsoft once AGI is attained is that unfettered access to OpenAI intellectual property could unduly concentrate power in the tech giant. In order to incentivize it for investing billions in the non-profit, which would have never gone public, Microsoft’s current agreement with OpenAI entitles it and other investors to take a slice of profits until they collect $100 billion. The cap is meant to ensure most profit eventually goes back to building products that benefit the entirety of humanity. This is all pie-in-the-sky thinking since, again, AI is not that powerful at this point.

It has been clear for some time that OpenAI does not care about public benefit, and the company has been looking to pivot into a for-profit structure, while maintaining its mission to benefit all of humanity, somehow, because the current non-profit structure makes it difficult to raise the huge amounts of money needed to compete. Consequently, The Information says Microsoft and OpenAI have been negotiating a host of changes to their arrangement that would go into place should the company restructure. Microsoft currently serves as OpenAI’s exclusive cloud hosting provider, and OpenAI may want to end that as well as stop profit-sharing and switch to simply giving Microsoft equity.

Microsoft and OpenAI have been on diverging paths for some time now. It was recently reported that the latter has begun incorporating AI models developed in-house into its 365 Copilot product in order to improve cost and efficiency. It doesn’t make sense for Microsoft to continue relying on OpenAI, an independent company developing similar productivity tools, for technology that it believes will be the backbone of its productivity software going forward. Especially with all the chaos and drama that has surrounded OpenAI. That is probably why it is not continuing to fund OpenAI. Microsoft needs its own proprietary tech to chart its own path.

OpenAI is far away from achieving that $100 billion in profit milestone – it is expected to generate $4 billion in revenue for 2024 – on technology whose true value remains speculative, which means under the current arrangement it would likely have to keep handing its technology and profits over to Microsoft for a long time. That is not great as they head towards becoming competitors and OpenAI seeks new investors. Getting rid of the cloud hosting tie-up could also allow OpenAI to negotiate better hosting costs with an alternative provider, something Google has told the FTC in a letter imploring it to nullify the agreement.

Elon Musk, a co-founder of OpenAI and former board member, has been suing to try and stop the company from converting into a for-profit entity. He has argued, among other things, that he invested roughly $50 million into the company in its early days believing it would be a non-profit in perpetuity, and now feels deceived. He has also complained in court that OpenAI pays exorbitant salaries in a way that is intended to thwart rivals and therefore anti-competitive. Because Musk has launched his own competing AI startup, xAI, skeptics think his lawsuit is a thinly veiled attempt at slowing down OpenAI’s growth.

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As Musk looks to colonise Mars it’s going to need its own communications and satellite networks.

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As Elon Musk eyes sending colonists to Mars entrepreneurs are starting to think about how they’d be supported and how they’d pay for goods – as well as communicate with Earth. So, naturally NASA is hunting for a partner capable of equipping Mars with steady internet connectivity, and SpaceX is convinced it’s the right company for the job. A presentation shared Thursday reveals that SpaceX is working on a Mars iteration of Starlink called “Marslink,” which would use dedicated satellites to relay information to and from the Red Planet.

Whether or not humans colonize Mars in the coming years, we’ll need to supply our dusty planet with an updated communication channel. Today’s Mars explorers use other missions’ satellites to send information back to Earth: Curiosity or Perseverance sends data to NASA’s MRO or MAVEN, which are otherwise busy studying the planet’s composition, and then MRO or MAVEN relays the signal to a network of Earth antennae called the Deep Space Network (DNS). Although this system works right now, it isn’t robust enough to support the myriad Mars missions various space entities are dreaming up – especially if humans ever find a way to live among all of that red dirt.

The Future of Space, by Futurist Keynote Matthew Griffin

To get ahead of the challenge, NASA has called on commercial space organizations to pitch how they would manage “next-generation relay services” for Mars. A slide deck shared by Spaceflight Now offers a peek at Marslink, a constellation of Starlink-like satellites that would orbit Mars and provide connectivity for both ground and orbital missions. NASA requires pitched relay systems to be capable of at least 4 megabytes per second (Mbps) of data transfer, and the slide alleges that Marslink exceeds this threshold, with extra capacity for imaging and monitoring.

SpaceX’s plan for Mars internet competes with pitches from Blue Origin and Lockheed Martin. Blue Origin’s plan involves a spacecraft platform called Blue Ring, which the company says offers hosting, data relay, and “in-space cloud computing.” Lockheed’s idea meanwhile incorporates its MAVEN spacecraft design.

It’s unclear whether NASA is committed to choosing one of these plans in the near term or simply exploring commercial options; the organization’s “Exploring Mars Together” slide deck insinuates both. Based on one slide in particular, it’s possible that SpaceX, Blue Origin, or Lockheed will be awarded a study contract that allows it to flesh out a plan, conduct research, or develop a prototype solution.

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The US debt burden will bankrupt the country says Musk, could Bitcoin pay it all off?!

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“Excess government spending is driving America into bankruptcy,” Musk posted to X, the social media platform he bought and rebranded from Twitter, adding: “This debt growth is unsustainable.” And many people, including in the Pentagon where one way to break the US military is to bankrupt them first, agree.

Musk was replying to Bitcoin-backing Kentucky senator Rand Paul, who called the “status quo of $2 trillion annual deficits unsustainable.”

Paul made headlines in 2015 when he began accepting bitcoin campaign donations to support his Republican White House bid – with Donald Trump and many other 2024 candidates following suit – and in 2021 said in an interview he believed crypto could replace the US dollar due to a lack of confidence in the currency and increased government surveillance.

U.S. national debt has skyrocketed in recent years, crossing the $34 trillion mark at the beginning of 2024, largely due to Covid and lockdown stimulus measures that sent inflation spiralling out of control and forced the Federal Reserve to hike interest rates at a historical clip.

Earlier this year, Trump floated the idea he could use bitcoin to “pay off our $35 trillion – hand them a little crypto check, right? We’ll hand them a little bitcoin and wipe out our $35 trillion,” he said.

In July, Trump promised to create a “strategic national bitcoin reserve” and predicted bitcoin could eclipse gold’s $16 trillion market capitalization during an appearance at the Bitcoin 2024 conference.

Musk’s campaign against excessive US spending has resulted in calls for the creation of the Doge Department Of Government Efficiency, which Musk has said he believes could strip $2 trillion from US spending.

The Doge department is a nod to the shiba inu doge meme that’s also linked to the dogecoin cryptocurrency, named by Elon Musk as his “favourite” cryptocurrency and accepted as payment by his Tesla car company.

Doge’s association with the dogecoin bitcoin rival has caused the dogecoin price to more than double over the last month, with billionaire Mark Cuban joking Musk could put dogecoin in the US Treasury.

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AI is taking huge amounts of compute and energy to train and now Oracle have broken the Zettascale barrier.

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Oracle today announced the launch of world’s first Zettascale Artificial Intelligence (AI) cloud computing clusters – where Zettascale computing in AI is different from Zettascale in actual HPC land –  beating the Japanese government and Fujitsu to the punch, which in this case is  powered by NVIDIA Blackwell GPUs offering up to 131,072 GPUs and delivering 2.4 zettaFLOPS of peak performance.

Oracle’s robust AI infrastructure, powered by NVIDIA GPUs, enables businesses to handle large-scale AI workloads with enhanced flexibility and sovereignty.

“We have one of the broadest AI infrastructure offerings and are supporting customers that are running some of the most demanding AI workloads in the cloud,” said Mahesh Thiagarajan, EVP of Oracle Cloud Infrastructure.

The Future of AI and Generative AI, by keynote Matthew Griffin

By combining NVIDIA’s advanced GPU architecture with Oracle’s cloud infrastructure, they’re offering scalable AI computing solutions critical for businesses and researchers globally.

“NVIDIA’s full-stack AI computing platform on Oracle’s broadly distributed cloud will deliver AI compute capabilities at unprecedented scale,” said Ian Buck, VP of Hyperscale and HPC, NVIDIA.

This new development from Oracle supports advanced AI research and development while ensuring regional data sovereignty, a crucial factor for industries like healthcare and collaboration platforms such as Zoom and WideLabs among others. Oracle Cloud Infrastructure (OCI) offers up to 131,072 NVIDIA B200 GPUs, which is six times more than other cloud hyperscalers like AWS, Azure, and Google Cloud.

For example, while AWS UltraClusters can host up to 20,000 GPUs, OCI offers more than three times that amount, enabling unprecedented levels of computational power.

Oracle also claimed that it is first to offer a zettascale AI supercomputer, delivering 2.4 zettaFLOPs while competitors have only reached exascale levels.

Moreover, OCI supports a wide range of GPUs, including NVIDIA H200, B200, and GB200 GPUs, with general availability across multiple architectures (Hopper, Blackwell) and the ability to run AI workloads of varying scales.

OCI will be the first to offer NVIDIA GB200 Grace Blackwell Superchips, which are designed for 4x faster training and 30x faster inference compared to H100 GPUs. This is important for AI model requiring real-time inference and multimodal LLM training.

That explains why OpenAI recently partnered with OCI to expand its capacity for running ChatGPT, leveraging its AI infrastructure to meet the rising demand for generative AI services, alongside its collaboration with Microsoft Azure.

“Leaders like OpenAI are choosing OCI because it is the world’s fastest and most cost-effective AI infrastructure,” said Larry Ellison, Oracle Chairman and CTO. Now with its supercluster scaling up to 131,072 NVIDIA B200 GPUs, there is no stopping Oracle and OpenAI.

“OCI will extend Azure’s platform and enable OpenAI to continue to scale,” said OpenAI’s chief Sam Altman.

Despite the happy news though Elon Musk is not smiling after Oracle and Elon Musk’s AI startup xAI recently ended talks on a potential $10 billion cloud computing deal, with xAI opting to build its own data center in Memphis, Tennessee.

At the time, Musk emphasised the need for speed and control over its own infrastructure. “Our fundamental competitiveness depends on being faster than any other AI company. This is the only way to catch up,” he added.

xAI is constructing its own AI data center with between 100,000 and 300,000 NVIDIA B200 chips. It claimed that it will be the world’s most powerful AI training cluster, marking a significant shift in strategy from cloud reliance to full infrastructure ownership.

After Microsoft Azure and Google Cloud, Oracle has finally partnered with AWS to launch Oracle Database@AWS, enabling customers to access Oracle Autonomous Database and Exadata services on AWS infrastructure.

“To meet this demand and give customers the choice and flexibility they want, Amazon and Oracle are seamlessly connecting AWS services with the very latest Oracle Database technology, including the Oracle Autonomous Database,” said Larry Ellison, Oracle Chairman and CTO.

The partnership offers zero-ETL integration and unified support, helping businesses modernise and improve outcomes.

“This partnership provides customers with a unified experience for migrating and managing their Oracle databases,” said AWS chief Matt Garman.

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As renewable energy is rolled out globally it still needs massive amounts of Grid Scale Storage, and this is Tesla’s largest battery storage by far globally.

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Tesla has secured an absurdly large contract to provide over 15 GWh of Megapack to California’s Intersect Power. The Megapack has become the go-to, poster child product for large-scale energy storage around the globe.

It’s by far Tesla’s fastest-growing product and enabled the company to deploy a record of 9.4 GWh of energy storage last quarter – more than twice the last record.

Now, Tesla has secured its biggest Megapack contract to date and it is absurdly large. Today, Intersect Power announced that it secured a contract for Tesla to provide them 15.3 GWh of Megapacks through the next 5 years.

Intersect Power wrote in a press release: “Tesla and Intersect Power today announced a contract for 15.3 GWh of Megapacks, Tesla’s battery energy storage system, for Intersect Power’s solar + storage project portfolio through 2030. This agreement, when combined with previous commitments, make Intersect Power one of the largest buyers and operators of Megapacks globally with nearly 10 GWh of large-scale energy storage expected to be deployed by the end of 2027.”

As mentioned above, most of that capacity is expected to be deployed within the next 2 years, which means a significant part of Tesla’s capacity, which is currently ramping to 40 GWh per year, is going to go to Intersect.

Intersect currently only “2.2 GW of operating solar PV and 2.4 GWh of grid scale storage in operation or construction.” So this is a big step up for them, but the 10 GWh of projects planned for the next 2 years are reportedly already in the pipeline.

Mike Snyder, Senior Director of Tesla Energy, commented on the new partnership with Intersect: “Intersect continues to be an exceptional partner, and their development expertise combined with the plug-and-play nature of Tesla’s vertically integrated technology enables the speed and scale needed to enhance grid resilience and support greater renewables integration.”

Sheldon Kimber, CEO of Intersect Power, added: “No one in the market can match Tesla’s depth of experience in storage technology. This partnership is the foundation of one of the largest and fastest growing storage portfolios in the country here at Intersect Power. This storage franchise is the perfect complement to our multi-billion dollar expansion of renewable generation that is expected to more than triple the size of our company over the next three years.”

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Increasingly neural implants are helping people regain the ability to see, feel, move, and much more.

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Neuralink owner Elon Musk says that a new BlindSight device that helps restore peoples sight – even for those who’ve been blind since birth or even those who have ‘lost both eyes and their optic nerve’ – just got a big boost after it received a Breakthrough Device Designation from the US Food and Drug Administration (FDA), which will help speed up its development.

Neuralink kept the details of the new device vague and said it could “bring back sight to those who have lost it” and Musk claimed it could enable “even those who have lost both eyes and their optic nerve to see.”

“Provided the visual cortex is intact, it will even enable those who have been blind from birth to see for the first time,” Musk said.

In an X post he said the vision from this device will initially be at “low resolution,” but then claimed it could eventually become better than natural vision and “enable you to see in infrared, ultraviolet or even radar wavelengths,” like some of the cyborg-like implants that I’ve talked about before.

The company has a long way to go before those claims can be proven true or false, but the FDA designation is a boost for Blindsight’s progress to market. The Breakthrough Devices programme aims to give patients and healthcare providers timely access to medical devices by speeding up the development, assessment and review of devices for premarket approval.

This marks another victory for Neuralink, which has been focused on a human trial for a brain-implant device that lets people interact with devices without needing to use of their limbs. Two patients have been implanted with this device so far and the company has shared exciting progress on both of these individuals.

Neuralink received FDA approval last year to run clinical trials on humans, in the form of an investigational device exemption. This allows devices to be used in a clinical study in order to collect “safety and effectiveness data.”

The company has trialled the technology with pigs and monkeys over the years, with one monkey making headlines when it was shown playing the classic video game Pong with its mind. But like many companies associated with Musk, Neuralink has been hit with controversy in the past. The company faced federal investigation in the US for potential animal welfare violations during its trials.

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What if you could compartmentalise your mind so that different parts of it work on different things in parallel … in the latest examples this is making neural implant patients much more cognitively capable.

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In a recent unveiling by Neuralink, the world witnessed an impressive leap in Brain Machine Interface (BMI) technology, as demonstrated by Noland Arbaugh, a 29-year-old man paralyzed from the shoulders down. This event not only marked a significant milestone in the application of neural implants but also introduced an interesting concept that some psychologists are terming “cognitive compartmentalization.”

Cognitive compartmentalization, as showcased by Arbaugh, is not merely a technological event; it represents a curious evolution of human cognition. It involves the ability to segregate and manage multiple conscious cognitive processes simultaneously, such as articulating thoughts while independently controlling a digital interface through mental commands. And while the multi-tasking of human thought and activity is commonplace, this new capability may suggest a remarkable expansion in our cognitive capacities, potentially heralding a new forefront in human-computer symbiosis, or as Elon Musk referred to it as AI Symbiosis, and a technological push on the complexity of human capabilities.

But let’s take a cognitive step back. Compartmentalization, in psychological terms, refers to a defense mechanism where individuals mentally separate conflicting thoughts, emotions, or experiences to avoid cognitive dissonance and emotional discomfort. This process allows people to hold contradictory beliefs or emotions by isolating them into distinct compartments within their minds, preventing them from clashing and causing distress. It’s a subconscious effort to maintain mental integrity and emotional equilibrium in the face of conflicting internal or external demands.

On the other hand, the term “cognitive compartmentation,” as researchers presented it in the context of Neuralink’s groundbreaking demonstration, extends beyond this traditional defense mechanism to encompass a deliberate, conscious, and technologically augmented expansion of cognitive processes. This novel and speculative concept describes the ability to consciously manage and operate multiple streams of thought or tasks simultaneously, facilitated by advanced neural implants.

This distinction is pivotal. While traditional compartmentalization serves as a psychological coping strategy to manage internal conflicts and maintain emotional stability, cognitive compartmentation represents a technologically-mediated leap in cognitive capability. It suggests a potential reconfiguration of cognitive architecture, where the brain, augmented by technological interfaces, can engage with and process multiple streams of information simultaneously, akin to running several complex software applications on a computer without compromising the performance of each.

This expansion in cognitive capability through “cognitive compartmentation” challenges our current understanding of the human mind’s limitations and opens up new frontiers in exploring consciousness, multitasking, and the integration of Artificial Intelligence (AI) with human cognitive processes. It propels us into a future where the delineation between human cognition and machine intelligence becomes increasingly blurred, suggesting extraordinary advancements in how we interact with digital environments, solve complex problems, and experience the world around us.

This capacity could fundamentally alter our approach to multitasking, creativity, problem-solving, and even the essence of human experience and work. From a medical perspective, it offers a beacon of hope for individuals with motor neuron diseases, spinal cord injuries, and other conditions that impair physical capabilities. From a philosophical standpoint, it challenges our understanding of consciousness, free will, and the nature of human-machine interaction.

While the advent of cognitive compartmentalization may reflect a new perspective on human cognitive capability, it’s important to consider the potential ramifications of such expanded functionality. This proliferation of mental multitasking could usher us into a realm of fractured realities, where the seamless integration of digital interfaces and neural processes might stretch the fabric of our cognitive capacity into uncertain territory.

The human brain, while remarkably adaptable, operates within the confines of evolutionary parameters that have historically been bounded by the tangible world. The introduction of a layer where thoughts directly influence digital actions could lead to a dissonance between our physical reality and the digital realms we interact with. This disjunction might not only challenge our perception of reality but also strain our cognitive resources, leading to a potential overload or diffusion of focus.

From the researchers viewpoint many see the potential emergence of a “Cognitive Multiverse” where neural implants and AI partner to expand thought into to a rich and more multifaceted experience. This expansion through cognitive compartmentalization represents a fascinating view into our understanding of human potential. Neuralink’s recent demonstration is not just a testament to technological advancement; it is a portal to a future where the limitations of human cognition may be completely redefined.

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WHY THIS MATTERS IN BRIEF

As AI models get even bigger and more energy hungry buyers are lining up around the block for Nvidia’s latest ultra-powerful GPUs.

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Artificial Intelligence (AI) GPU development is running at breakneck speeds, and Elon Musk wants to be at the forefront of the revolution. In an X post, the SpaceX and Tesla CEO revealed that he wants to buy 300,000 worth of Nvidia’s latest Blackwell B200 GPUs by next summer. The new GPUs will upgrade X’s existing AI GPU cluster, which currently consists of 100,000 previous-generation H100 GPUs.

100,000 H100 GPUs is already an enormous amount of computing power, but Elon states that given the pace of AI GPU development, it’s not worth keeping around X’s massive array of H100 GPUs for long, mainly due to its energy consumption of 1 Gigawatt – which is huge!

X uses the massive array of AI GPUs for Grok, an AI bot. The AI was developed on a homebrewed language dubbed Grok-1 that is geared to provide less straightforward answers as well as witty and comedic answers compared to ChatGPT and Gemini. Basically, it is trying to take the “robot” aspect out of the AI bot. The new AI bot is available to X users right now; however, you’ll need to be an X Premium user to gain access to the AI bot.

Musk’s logic has merit. The AI GPU development race is one of the most heated races we’ve seen in years in the technological industry, rivalling the CPU development wars we had in the 1990s and 2000s. Nvidia’s new Blackwell B200 is a massive upgrade over the H100, offering four times the training performance and 30 times the inference performance.

Technically, the B200 does consume more power. However, the B200’s colossal performance improvements mean the chip runs significantly more efficiently than the H100. In Musk’s case, trading 100,000 H100s for three times more GPUs that consume even more power is still a net win due to the GPUs’ incredible amount of additional AI performance.

It’ll be interesting to see when Musk does get his hands on all 300,000 B200 GPUs. If Nvidia’s H100 has taught us anything, it’s that its AI GPU demand always outstrips actual supply. We will probably see a repeat of 2023, when all the big AI customers, including X, Meta, Google, Microsoft, and others, are fighting to grab as many B200s as Nvidia can pump out for at least the next several months.

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