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Beyond AI: Building toward artificial consciousness Part I – CIO

As the race to deploy artificial intelligence (AI) hits a fever pitch across enterprises, the savviest organizations are already looking athowto achieve artificial consciousnessa pinnacle of technological and theoretical exploration. However, this undertaking requires unprecedented hardware and software capabilities, and while systems are under construction, the enterprise has a long way to go to understand the demandsand even longer before it can deploy them. This piece is the first in a series of three articles outlining the parameters for artificial consciousness.

The hardware requirements include massive amounts of compute, control, and storage. These enterprise IT categories are not new, but the performance requirements are unprecedented. While enterprises have experience deploying compute, control, and storage requirements for Software-as-a-Service (SaaS)-based applications in a mobile-first and cloud-first world, they are learning how to scale these hardware requirements for AI environments and, ultimately, systems that can deliver artificial consciousness nirvana.

It all starts with compute capacity

As Lenovos third annualglobal CIO reportrevealed, CIOs are developing their AI roadmaps now and assessing everything from their organizational support to capacity building to future-forward investment in tech. The first requirement CIOs must meet when considering artificial consciousness is compute capacity, which falls under capacity building. The amount of compute needed is much more intensive than AI or even GenAI given the sheer volume of data required to enable systems that are fully capable of learning and reasoning.

The higher processing power is achieved by leveraging a compute fabric comprised of sophisticated server clusters. This approach is familiar to CIOs that have deployed high-performance computing (HPC) infrastructure. These clusters seamlessly integrate advanced hardware to deliver unparalleled processing power and efficiency.

At the heart of this cluster-based infrastructure configuration is the concept of a pod, meticulously organized to maximize computing density and thermal efficiency. Each pod comprises 16 racks, with each rack housing eight water-cooled serversa configuration that ensures not only optimal performance but also environmental sustainability through the advanced cooling capabilities. These high-powered servers feature 2TB of DDR5 registered DIMM ECC system memory to ensure rapid access to data and combine the direct water cooling with a rear door heat exchanger that captures residual waste heat. These state-of-the-art servers are customizable with the latest GPUs or AI processors available from Nvidia, AMD, or Intel, providing massive parallel computing power for this extremely demanding application.

Each 16-rack pod also includes a Vertiv end-of-row coolant distribution unitan innovative component designed to efficiently manage the thermal dynamics of high-density computing environments and ensure this high-powered hardware operates within safe thermal thresholds. The result is a system that delivers high performance and reliability while also significantly boosting energy efficiency. By reducing the overall cooling power requirements, each pod is both powerful and environmentally conscious.

Laying the foundation for artificial consciousness

The quest to build artificial consciousness is ambitious, as maximizing the groundbreaking algorithms introduces a whole new set of hardware infrastructure requirementsthe first of which is compute power. Once an enterprise scales its processing power, it must also scale its control and storage hardware before it can activate the advanced software stacks and strategic services that will operationalize artificial consciousness. The next article in the series will look at how to build capacity for higher control and storage hardware requirements.

Learn how Lenovo unlocks the power for AI for enterprises.

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SoftBank CEO says AI that is 10000 times smarter than humans will come out in 10 years – CNBC

Masayoshi Son, chairman and chief executive officer of SoftBank Group Corp., speaks during the company's annual general meeting in Tokyo, Japan, on Friday, June 20, 2024. Son sketched out ambitions to help create AI thousands of times smarter than any human, making his most grandiose pronouncements since the Japanese conglomerate began taking steps to shore up its finances following a series of ill-timed startup bets.

Kosuke Okahara | Bloomberg | Getty Images

Artificial intelligence that is 10,000 times smarter than humans will be here in 10 years, SoftBank CEO Masayoshi Son said on Friday, in a rare public appearance during which he questioned his own purpose in life.

Son laid out his vision for a world featuring artificial super intelligence, or ASI, as he dubbed it.

The CEO first talked about another term artificial general intelligence, or AGI which broadly refers to AI that is smarter than humans. Son said this tech is likely to be one to 10 times smarter than humans and will arrive in the next three-to-five years, earlier than he had anticipated.

But if AGI is not much smarter than humans, "then we don't need to change the way of living, we don't need to change the structure of human lifestyle," Son said, according to a live translation of his comments in Japanese, which were delivered during SoftBank's annual general meeting of shareholders.

"But when it comes to ASI it's a totally different story. [With] ASI, you will see a big improvement."

Son discussed how the future will hold various ASI models that interact with each other, like neurons in a human brain. This will lead to AI that is 10,000 times smarter than any human genius, according to Son.

SoftBank shares closed down more than 3% in Japan, following the meeting.

Son is SoftBank's founder, who rose to prominence after an early and profitable investment in Chinese e-commerce giant Alibaba. He positioned SoftBank as a tech visionary with the 2017 launch of the Vision Fund, a massive investment fund focused on backing tech firms. While some of the bets were successful, there were also many high-profile failures, such as office sharing company WeWork.

After posting then-record financial losses at Vision Fund in 2022, Son said that SoftBank would go into "defense" mode and be more conservative with its investments. In 2023, the Vision Fund posted a new record loss, with Son shortly after saying that SoftBank would now shift into "offense," because he was excited about the investment opportunities in AI.

Son has been broadly out of the public eye since then.

He returned to the spotlight on Friday to deliver a speech that was full of existential questions.

"Two years ago, I am getting old, rest of my life is limited, but I haven't done anything yet and I cried so hard," Son said, suggesting he feels he hasn't achieved anything of consequence to date.

He added that he had now found SoftBank's mission, which is the "evolution of humanity." He also said he has discovered his own purpose in life.

"SoftBank was founded for what purpose? For what purpose was Masa Son born? It may sound strange, but I think I was born to realize ASI. I am super serious about it," Son said.

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SoftBank CEO says AI that is 10000 times smarter than humans will come out in 10 years - CNBC

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AI doomers have warned of the tech-pocalypse while doing their best to accelerate it – Salon

One of the most prominent narratives about AGI, or artificial general intelligence, in the popular media these days is the AI doomer narrative. This claims that were in the midst of an arms race to build AGI, propelled by a relatively small number of extremely powerful AI companies like DeepMind, OpenAI, Anthropic, and Elon Musks xAI (which aims to design an AGI that uncovers truths about the universe by eschewing political correctness). All are backed by billions of dollars: DeepMind says that Microsoft will invest over $100 billion in AI, while OpenAI has thus far received $13 billion from Microsoft, Anthropic has $4 billion in investments from Amazon, and Musk just raised $6 billion for xAI.

Many doomers argue that the AGI race is catapulting humanity toward the precipice of annihilation: if we create an AGI in the near future, without knowing how to properly align the AGIs value system, then the default outcome will be total human extinction. That is, literally everyone on Earth will die. And since it appears that were on the verge of creating AGI or so they say this means that you and I and everyone we care about could be murdered by a misaligned AGI within the next few years.

These doomers thus contend, with apocalyptic urgency, that we must pause or completely ban all research aiming to create AGI. By pausing or banning this research, it would give others more time to solve the problem of aligning AGI to our human values, which is necessary to ensure that the AGI is sufficiently safe. Failing to do this means that the AGI will be unsafe, and the most likely consequence of an unsafe AGI will be the untimely death of everyone on our planet.

The doomers contrast with the AI accelerationists, who hold a much more optimistic view. They claim that the default outcome of AGI will be a bustling utopia: well be able to cure diseases, solve the climate crisis, figure out how to become immortal, and even colonize the universe. Consequently, these accelerationists some of whom use the acronym e/acc (pronounced ee-ack) to describe their movement argue that we should accelerate rather than pause or ban AGI research. There isnt enough money being funneled into the leading AI companies, and calls for government regulation are deeply misguided because theyre only going to delay the arrival of utopia.

Some even contend that any deceleration of AI will cost lives. Deaths that were preventable by the AI that was prevented from existing is a form of murder. So, if you advocate for slowing down research on advanced AI, you are no better than a murderer.

The loudest voices within the AI doomer camp have been disproportionately responsible for launching and sustaining the very technological race that they now claim could doom humanity.

But theres a great irony to this whole bizarre predicament: historically speaking, no group has done more to accelerate the race to build AGI than the AI doomers. The very people screaming that the AGI race is a runaway train barreling toward the cliff of extinction have played an integral role in starting these AI companies. Some have helped found these companies, while others provided crucial early funding that enabled such companies to get going. They wrote papers, books and blog posts that popularized the idea of AGI and organized conferences that inspired interest in the topic. Many of those worried that AGI will kill everyone on Earth have gone on to work for the leading AI companies, and indeed the two techno-cultural movements that initially developed and promoted the doomer narrative namely, Rationalism and Effective Altruism have been at the very heart of the AGI race since its inception.

In a phrase, the loudest voices within the AI doomer camp have been disproportionately responsible for launching and sustaining the very technological race that they now claim could doom humanity in the coming years. Despite their apocalyptic warnings of near-term annihilation, the doomers have in practice been more effective at accelerating AGI than the accelerationists themselves.

Consider a few examples, beginning with the Skype cofounder and almost-billionaire Jaan Tallinn, who also happens to be one of the biggest financial backers of the Rationalist and Effective Altruist (EA) movements. Tallinn has repeatedly claimed that AGI poses an enormous threat to the survival of humanity. Or, in his words, it is by far the biggest risk facing us this century bigger than nuclear war, global pandemics or climate change.

In 2014, Tallinn co-founded a Boston-based organization called the Future of Life Institute (FLI), which has helped raise public awareness of the supposedly grave dangers of AGI. Last year, FLI released an open letter calling on all AI labs to immediately pause for at least 6 months the training of AI systems more powerful than GPT-4, where GPT4 was the most advanced system that OpenAI had released at the time. The letter warns that AI labs have become locked in an out-of-control race to develop and deploy ever more powerful digital minds that no one not even their creators can understand, predict, or reliably control, resulting in a dangerous race. Tallinn was one of the first signatories.

Tallinn is thus deeply concerned about the race to build AGI. Hes worried that this race might lead to our extinction in the near future. Yet, through his wallet, he has played a crucial role in sparking and fueling the AGI race. He was an early investor in DeepMind, which Demis Hassabis, Shane Legg and Mustafa Suleyman cofounded 2010 with the explicit goal of creating AGI. After OpenAI started in 2015, he had a close connection to some people at the company, meeting regularly with individuals like Dario Amodei, a member of the EA movement and a key figure in the direction of OpenAI. (Tallinn himself is closely aligned with the EA movement.)

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In 2021, Amodei and six other former employees of OpenAI founded Anthropic, a competitor of both DeepMind and OpenAI. Where did Anthropic get its money? In part from Tallinn, who donated $25 million and led a $124 million series A fundraising round to help the company get started.

Here we have one of the leading voices in the doomer camp claiming that the AGI race could result in everyone on Earth dying, while simultaneously funding the biggest culprits in this reckless race toward AGI. Im reminded of something that Noam Chomsky once said in 2002, during the early years of George Bushs misguided War on Terror. Chomsky declared: We certainly want to reduce the level of terror, he said, referring to the U.S. There is one easy way to do that stop participating in it. The same idea applies to the AGI race: if AI doomers are really so worried that the race to build AGI will lead to an existential catastrophe, then why are they participating in it? Why have they funded and, in some cases, founded the very companies responsible for supposedly pushing humanity toward the precipice of total destruction?

In fact, Amodei, Shane Legg, Sam Altman and Elon Musk all of whom founded or cofounded some of the leading AI companies have expressed doomer concerns that AGI could annihilate our species in the near term. In an interview with the EA organization 80,000 Hours, Amodei referenced the possibility that an AGI could destroy humanity, saying I cant see any reason in principle why that couldnt happen. He adds that this is a possible outcome and at the very least as a tail risk we should take it seriously.

Over and over again, the very same people saying that AGI could kill us all have done more than anyone else to launch and accelerate the race toward AGI.

Similarly, DeepMind cofounder Shane Legg wrote on the website LessWrong in 2011 that AGI is his number 1 risk for this century. That was one year after DeepMind was created. In 2015, the year he co-founded OpenAI with Elon Musk and others, Altman declared that I think AI will most likely sort of lead to the end of the world, adding on his personal blog that the development of superhuman machine intelligence is probably the greatest threat to the continued existence of humanity.

Then theres Musk, who has consistently identified AGI as the biggest existential threat, and far more dangerous than nukes. In early 2023, Musk signed the open letter from FLI calling for a six month pause on advanced AI research. Just four months later, he announced that he was starting yet another AI company: xAI.

Over and over again, the very same people saying that AGI could kill us all have done more than anyone else to launch and accelerate the race toward AGI. This is even true of the most famous doomer in the world today, a self-described genius named Eliezer Yudkowsky. In a Time magazine article from last year, Yudkowsky argued that our only hope of survival is to immediately shut down all of the large computer farms where the most powerful AIs are refined. Countries should sign an international treaty to halt AGI research and be willing to engage in military airstrikes against rogue datacenters to enforce this treaty.

Yudkowsky is so worried about the AGI apocalypse that he claims we should be willing to risk an all-out thermonuclear war that kills nearly everyone on Earth to prevent AGI from being built in the near future. He then gave a TED talk in which he reiterated his warnings: if we build AGI without knowing how to make it safe and we have no idea how to make it safe right now, he claims then literally everyone on Earth will die.

Yet I doubt that any single individual has promoted the idea of AGI more than Yudkowsky himself. In a very significant way, he put AGI on the map, inspired many people involved in the current AGI race to become interested in the topic, and organized conferences that brought together early AGI researchers to cross-pollinate ideas.

Consider the Singularity Summit, which Yudkowsky co-founded with the Google engineer Ray Kurzweil and tech billionaire Peter Thiel in 2006. This summit, held annually until 2012, focused on the promises and perils of AGI, and included the likes of Tallinn, Hassabis, and Legg on its list of speakers. In fact, both Hassabis and Legg gave talks about AGI-related issues in 2010, shortly before co-founding DeepMind. At the time, DeepMind needed money to get started, so after the Singularity Summit, Hassabis followed Thiel back to his mansion, where Hassabis asked Thiel for financial support to start DeepMind. Thiel obliged, offering Hassabis $1.85 million, and thats how DeepMind was born. (The following year, in 2011, is when Tallinn made his early investment in the company.)

If not for Yudkowskys Singularity Summit, DeepMind might not have gotten off the ground or at least not when it did. Similar points could be made about various websites and mailing lists that Yudkowsky created to promote the idea of AGI. For example, AGI has been a major focus of the community blogging website LessWrong, created by Yudkowsky around 2009. This website quickly became the online epicenter for discussions about how to build AGI, the utopian future that a safe or aligned AGI could bring about, and the supposed existential risks associated with AGIs that are unsafe or misaligned. As noted above, it was on the LessWrong website that Legg identified AGI to be the number one threat facing humanity, and records show that Legg was active on the website very early on, sometimes commenting directly under articles by Yudkowsky about AGI and related issues.

Or consider the SL4 mailing list that Yudkowsky created in 2001, which described itself as dedicated to advanced topics in transhumanism and the Singularity, including strategies to accelerate the Singularity. The Singularity is a hypothetical future event in which advanced AI begins to redesign itself, leading to a superintelligent AGI system over the course of weeks, days, or perhaps even minutes. Once again, Legg also contributed to the list, which indicates that the connections between Yudkowsky, the worlds leading doomer, and Legg, cofounder of one of the biggest AI companies involved in the AGI race, goes back more than two decades.

These are just a few reasons that Altman himself wrote on Twitter (now X) last year that Yudkowsky the worlds leading AI doomer has probably contributed more than anyone to the AGI race. In Altmans words, Yudkowsky got many of us interested in AGI, helped DeepMind get funding at a time when AGI was extremely outside the Overton window, was critical in the decision to start OpenAI, etc. He then joked that Yudkowsky may deserve the Nobel Peace Prize for this. (These quotes have been lightly edited to improve readability.)

Rationalists and EAs are also some of the main participants and contributors to the very race they believe could precipitate our doom.

Though Altman was partly trolling Yudkowsky for complaining about a situation the AGI race that Yudkowsky was instrumental in creating, Altman isnt wrong. As a New York Times article from 2023 notes, Mr. Yudkowsky and his writings played key roles in the creation of both OpenAI and DeepMind. One could say something similar about Anthropic, as it was Yudkowskys blog posts that convinced Tallinn that AGI could be existentially risky, and Tallinn later played a crucial role in helping Anthropic get started which further accelerated the race to build AGI. The connections and overlaps between the doomer movement and the race to build AGI are extensive and deep the more one scratches the surface, the clearer these links appear.

Indeed, I mentioned the Rationalist and EA movements earlier. Rationalism was founded by Yudkowsky via the LessWrong website, while EA emerged around the same time, in 2009, and could be seen as the sibling of Rationalism. These communities overlap considerably, and both have heavily promoted the idea that AGI poses a profound threat to our continued existence this century.

Yet Rationalists and EAs are also some of the main participants and contributors to the very race they believe could precipitate our doom. As noted above, Dario Amodei (co-founder of Anthropic) is an EA, and Tallinn has given talks at major EA conferences and donated tens of millions of dollars to both movements. Similarly, an Intelligencer article about Altman reports that Altman once embraced EA, and a New York Times profile describes him as the product of a strange, sprawling online community that began to worry, around the same time Mr. Altman came to the Valley, that artificial intelligence would one day destroy the world. Called rationalists or effective altruists, members ofthis movementwere instrumental in the creation of OpenAI.

Yet another New York Times article notes that the EA movement beat the drum so loudly about the dangers of AGI that many young people became inspired to work on the topic. Consequently, all of the major AI labs and safety research organizations contain some trace of effective altruisms influence, and many count believers among their staff members. The article then observes that no major AI lab embodies the EA ethos as fully as Anthropic, given that many of the companys early hires were effective altruists, and much of its start-up funding came from wealthy EA-affiliated tech executives not just Tallinn, but the co-founder of Facebook Dustin Moskovitz, who, like Tallinn, has donated considerably to EA projects.

There is a great deal to say about this topic, but the key point for our purposes is that the doomer narrative largely emerged out of the Rationalist and EA movements the very movements that have been pivotal in founding, funding and inspiring all the major AI companies now driving the race to build AGI.

Again, one wants to echo Chomsky in saying: if these communities are so worried about the AGI apocalypse, why have they done so much to create the very conditions that enabled the AGI race to get going? The doomers have probably done more to accelerate AGI research than the AI accelerationists that they characterize as recklessly dangerous.

How has this happened? And why? One reason is that many doomers believe that AGI will be built by someone, somewhere, eventually. So it might as well be them who builds the first AGI. After all, many Rationalists and EAs pride themselves on having exceptionally high IQs while claiming to be more rational than ordinary people, or normies. Hence, they are the best group to build AGI while ensuring that it is maximally safe and beneficial. The unfortunate consequence is that these Rationalists and EAs have inadvertently initiated a race to build AGI that, at this point, has gained so much momentum that it appears impossible to stop.

Even worse, some of the doomers most responsible for the AGI race are now using this situation to gain even more power by arguing that policymakers should look to them for the solutions. Tallinn, for example, recently joined the United Nations Artificial Intelligence Advisory Body, which focuses on the risks and opportunities of advanced AI, while Yudkowsky has defended an international policy that leaves the door open to military strikes that might trigger a thermonuclear war. These people helped create a huge, complicated mess, then turned around, pointed at that mess, and shouted: Oh, my! Were in such a dire situation! If only governments and politicians would listen to us, though, we just might be able to dodge the bullet of annihilation.

This looks like a farce. Its like someone drilling a hole in a boat and then declaring: The only way to avoid drowning is to make me captain.

The lesson is that governments and politicians should not be listening to the very people or the Rationalist and EA movements to which they belong that are disproportionately responsible for this mess in the first place. One could even argue plausibly, in my view that if not for the doomers, there probably wouldnt be an AGI race right now at all.

Though the race to build AGI does pose many dangers, the greatest underlying danger is the Rationalist and EA movements that spawned this unfortunate situation over the past decade and a half. If we really want to bring the madness of the AGI race to a stop, its time to let someone else have the mic.

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Bitcoin price today: slid to $61k amid dollar pressure, inflation jitters By Investing.com – Investing.com

Investing.com-- Bitcoin price slid lower on Monday, extending a deep decline from the past week as concerns over U.S. interest rates and anticipation of key inflation data kept traders largely biased towards the dollar.

Broader cryptocurrency prices were also pressured by a strong dollar, as the greenback came close to a two-month high following robust U.S. purchasing managers index data.

fell 4.9% in the past 24 hours to $61,233.4 by 08:37 ET (12:37 GMT).

The worlds largest cryptocurrency was nursing steep losses over the past week as traders grew skeptical over the timing of interest rate cuts by the Federal Reserve.

This sentiment is likely to see little signs of improvement this week, especially ahead of key data due this Friday.

The reading is the preferred inflation gauge of the Fed, and is likely to factor into the central banks outlook on interest rates in the coming months. While Fridays data is expected to show some mild cooling in inflation, the reading is still expected to remain well above the Feds 2% annual target- giving the central bank more headroom to keep rates high.

High rates bode poorly for crypto, given that they diminish the appeal of speculative, risk-driven assets such as crypto.

Major altcoins saw much deeper losses than Bitcoin, as a slew of token unlocks, dwindling institutional demand and a healthy dose of profit-taking pressured crypto prices.

Recent capital flow data showed institutional demand, especially for crypto investment products, remained centered largely around Bitcoin. But even Bitcoin was seen logging heavy outflows earlier in June.

World no.2 token dropped more than 5% to $3,320.76, hitting a one-month low as it largely consolidated gains made on hype over a spot Ether exchange-traded fund.

slipped 1.9%, while and slid 3.5% and 4.6%, respectively. Both tokens had seen some gains in recent sessions.

Among meme tokens, and fell 5.5% and 6.5%, respectively.

Defunct bitcoin exchange Mt. Gox said on Monday that it will begin distributing assets stolen from clients during a 2014 hack starting in the first week of July, a move that comes after years of moving deadlines.

Nobuaki Kobayashi, the Rehabilitation Trustee, stated on the Mt. Gox website, The Rehabilitation Trustee has been preparing to make repayments in Bitcoin and under the Rehabilitation Plan. The repayments will be made from the beginning of July 2024, adding that due diligence and safety steps are necessary before payments can proceed.

These repayments are expected to increase selling pressure on the bitcoin market. Early investors will receive assets now valued much higher than their pre-2013 entries, leading many to sell at least part of their holdings, according to traders.

Mt. Gox, once the worlds leading crypto exchange, handled over 70% of all bitcoin transactions in its early years. In early 2014, a hack resulted in the loss of approximately 740,000 bitcoin (worth $15 billion today). This was the largest of several attacks on the exchange between 2010 and 2013.

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How is AI transforming the insurtech sector? – Information Age

Artificial intelligence (AI) is impacting almost every industry, and insurance and the insurtech sector on which it depends is no exception, with applications benefiting both customers and insurance firms themselves.

From a customer service perspective, the use of chatbots is helping to answer queries in a more efficient manner, providing customers with instant answers around the clock, says Quentin Colmant, CEO of insurtech firm Qover. AI-powered chatbots can assist customers with contract management, freeing up human agents for more complex issues, he says. Additionally, AI analyses vast amounts of customer data to personalise insurance recommendations. This allows insurtechs to tailor products to the specific needs of customers, ensuring they are presented with the most relevant options.

The emergence of generative AI is likely to see this evolve further, using multiple data sources to provide even more personalised digital interaction. General information typically provided through static and dynamic FAQs are likely to be superseded by a more interactive human-style chatbot, which was on the increase even before the advent of generative AI, says Tony Farnfield, partner and UK practice lead at management consulting firm BearingPoint. The ability to link an AI bot to back-end policy and claims systems will scale back the need for human intervention.

Generative AI can also help target specific areas of frustration for customers, says Rory Yates, global strategic lead at EIS, referencing its own client esure Group. They focused on a key customer frustration when calling a contact centre, which was repetition, so being passed from one person to the next, and needing to re-explain the reason for making contact, he says. Their use of generative AI helps alleviate this. Then at the end of every call, generative AI is used to summarise the notes, capturing the details of the call, making sure accurate records are kept.

Internal efficiency is another major benefit of the effective use of AI. Steve Muylle, professor of digital strategy and business marketing at Vlerick Business School, gives the example of AI helping insurers to generate accurate quotes almost immediately. In 2019, Direct Line launched Darwin a motor insurance platform that uses AI to determine individual pricing through machine learning, he says. This approach has translated into better customer reviews and improved customer service.

Another example is in Asia, where insurance companies work with Uber, he adds. After an accident, insurers can ask nearby Uber drivers to check accidents, leveraging their knowledge of cars and their ability to take photos or videos for reporting, which can then be analysed by AI. This provides the insurers with more data, potentially from a third party, and is also a side gig for the Uber drivers.

Another application is in the onboarding and training of employees. AI-powered virtual assistants can guide new employees through the onboarding process, providing support and answering questions around the clock, says Christian Brugger, partner at digital consultancy OMMAX. Interactive AI-powered tools, such as virtual reality and augmented reality, can offer immersive training experiences, simulating real-life scenarios employees might face.

Its also being used to improve efficiency more generally, in the same way as it might any other business. The ability to automate high-volume, routine, low-value-added tasks has allowed insurers to speed up their services and increase productivity, says Steve Bramall, credit director at Allianz Trade. This frees up valuable experts to spend more time with customers and brokers, improving customer experience.

Yet the use of AI also brings risks and ethical considerations for insurers and insurtech firms. With all AI, you need to understand where the AI models are from and where the data is being trained from and, importantly, whether there is an in-built bias, says Kevin Gaut, chief technology officer at insurtech INSTANDA. Proper due diligence on the data is the key, even with your own internal data.

Its essential, too, that organisations can explain any decisions that are taken, warns Muylle, and that there is at least some human oversight. A notable issue is the black-box nature of some AI algorithms that produce results without explanation, he warns. To address this, its essential to involve humans in the decision-making loop, establish clear AI principles and involve an AI review board or third party. Companies can avoid pitfalls by being transparent with their AI use and co-operating when questioned.

AI applications themselves also raise the potential for organisations to get caught out in cyber-attacks. Perpetrators can use generative AI to produce highly believable yet fraudulent insurance claims, points out Brugger. They can also use audio synthesis and deepfakes pretending to be someone else. If produced at high-scale, such fraudulent claims can overwhelm the insurer, leading to higher payouts.

Cyber-attacks can also lead to significant data breaches, which can have serious consequences for insurers. These can expose confidential client information, which inevitably poses new challenges towards fostering client trust, says James Harrison, global head of insurance at Dun & Bradstreet. Additionally, failure to comply with data protection regulations, such as GDPR, can lead to legal consequences and financial penalties.

Having robust cybersecurity measures is essential, particularly when it comes to sensitive or personal data, says David Dumont, a partner at law firm Hunton Andrews Kurth, and its important to ensure these remain able to cope with new regulations. In the EU, the legal framework on cybersecurity is evolving and becoming more prescriptive, he explains. Within the next year, insurtechs may, for example, be required to comply with considerable cybersecurity obligations under the Digital Operational Resilience Act (DORA), depending on the specific type of products and services that they offer.

All this means AI requires careful handling if insurers and insurtechs are to realise the benefits, without experiencing the downsides. The future of AI in insurtech is brimming with potential, believes Colmant. AI will likely specialise in specific insurance processes, like underwriting or claims management, leading to significant efficiency gains and improved accuracy. This will also likely lead to even greater personalisation and automation.

However, the focus will likely shift towards a collaborative approach, with AI augmenting human capabilities rather than replacing them entirely. Throughout this evolution, ethical considerations will remain a top priority.

How artificial intelligence is helping to slash fraud at UK banks Rob Woods, fraud expert at LexisNexis Risk Solutions, tells Charles Orton-Jones why behavioural data and AI are a powerful fraud-fighting combination

Why is embedded insurance so popular right now? Charles Orton-Jones asks five industry experts how embedded insurance could transform the sector and whether or not it offers real value for consumers

Will more AI mean more cyberattacks? An increased use of AI within organisations could spell a rise in cyberattacks, explains Nick Martindale. Heres what you can do

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Multimodal AI: Turning a One-Trick Pony into Jack of All Trades – InformationWeek

Just when you think artificial intelligence could not do more to reduce mundane workloads, create content from scratch, sort through massive amounts of data to derive insights, or identify anomalies on an X-ray, along comes multimodal AI.

Until very recently, AI was mostly focused on understanding and processing singular text or image-based information a one-trick pony, so to speak. Today, however, theres a new entrant into the world of AI, a true jack of all trades in the form of multimodal AI. This new class of AI involves the integration of multiple modalities -- such as images, videos, audio, and text, able to process multiple data inputs.

What multimodal AI really delivers is context. Since it can recognize patterns and connections between different types of data inputs, the output is richer and more intuitive, getting closer to multi-faceted human intelligence than ever before.

Just as generative AI (GenAI) has done over the past year, multimodal AI promises to revolutionize almost all industries and bring a whole new level of insights and automation to human-machine interactions.

Already many Big Tech players are volleying to dominate multimodal AI. One of the most recent players is X (formerly Twitter), which launched Grok 1.5, which it claims outperforms its competitors when it comes to real-world spatial understanding. Other players include Apple MM1, Anthropic Claude 3, Google Gemini, Meta ImageBind and OpenAI GPT 4.

Related:Help Your C-Suite Colleagues Navigate Generative AI

While AI comes in many forms -- from machine learning and deep learning -- to predictive analytics and computer vision, the real showstopper for multimodal AI is computer vision. With multimodal AI, computer visions capabilities go far beyond simple object identification. With the ability to combine many types of data, the AI solution can understand the context of an image and make more accurate decisions. For example, the image of a cat, combined with audio of a cat meowing, gives it greater accuracy when identifying all images of cats. In another example, an image of a face, when combined with video can help AI not only identify specific people in photos, but greater contextual awareness.

Use cases for multimodal AI are just beginning to surface, and as it evolves it will be used in ways not even imaginable today. Consider some of the ways it is or could be applied:

Ecommerce. Multimodal AI could analyze text, images and video in social media data to tailor offerings to specific people or segments of people.

Automotive. Multimodal AI can improve the capabilities and safety of self-driving carsby combining data from multiple sensors, such as cameras, radar or GPS systems, for heightened accuracy.

Healthcare. It can use data from images and scans, electronic health records and genetic testing resultsto assist clinicians in making more accurate diagnoses. As well as more personalized treatment plans.

Finance. It can enable heightened risk assessment by analyzing data in various formats to get deeper insights and understanding of specific individuals and their risk level for mortgages, etc.

Conservation. Multimodal AI could identify whales from satellite imagery, as well as audio of whale sounds to track migration patterns and changing feeding areas.

Related:The AI Skills Gap and How to Address It

Multimodal AI is an exciting development,but it still has a long way to go. A fundamental challenge lies in integrating information from disparate sources cohesively. This involves developing algorithms and models capable of extracting meaningful insights from each modality and integrating them to generate comprehensive interpretations.

Another challenge is the scarcity of clean, labeled multimodal datasets for training AI models. Unlike single-modality datasets, which are more plentiful, multimodal datasets require annotations that capture correlations between different modalities, making their creation more labor-intensive and resource-intensive. Yet achieving the right balance between modalities is crucial for ensuring the accuracy and reliability of multimodal AI systems.

Related:AI, Data Centers, and Energy Use: The Path to Sustainability

As with other forms of AI, ensuring unbiased multimodal AI is a key consideration made more difficult because of the varied types of data. Regardless, diverse types of images, text, video, and audio need to be factored into the development of solutions, as well as the biases that can arise from the developers themselves.

Data privacy and protection also need to be considered, given the vast amount of personal data that multimodal AI systems may process. Questions could arise about data ownership, consent, and protection against misuse, when humans are not fully in control of the output of AI.

Addressing these ethical challenges requires a collaborative effort involving developers, government, industry leaders, and individuals. Transparency, accountability, and fairness must be prioritized throughout the development lifecycle of multimodal AI systems to mitigate their risks and foster trust among users.

Multimodal AI is bringing the capabilities of AI to new heights, enabling richer and deeper insights than previously possible. Yet, no matter how smart AI becomes, it can never replace the human mind and its many facets of knowledge, intuition, experience and reasoning -- AI still has a long way to go to achieve that, but its a start.

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Multimodal AI: Turning a One-Trick Pony into Jack of All Trades - InformationWeek

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Bitcoin falls below $61000 after one of its worst weeks this year – Quartz

Bitcoin dropped below $61,000 on Monday morning as the cryptocurrency continues to shed value.

The Fed needs to start cutting rates now, strategist says

Bitcoins price fell to as low as $60,818 its lowest level in more than a month in Monday morning trading in London. The cryptocurrencys price has dropped almost 4% in the past day, and has fallen roughly 8% over the last week.

Mondays slide comes after one of cryptos worst weeks of 2024 so far, as the global cryptocurrency market shed tens of billions of dollars in value. Overall, the global crypto market cap has slipped 4.7% in the last day, bringing its market cap to $2.24 trillion, according to CoinMarketCap. An index containing the 100 biggest cryptocurrencies fell about 5% in the week through Sunday, its steepest such decline since April, according to data compiled by Bloomberg.

Crypto watchers were eagerly anticipating new all-time highs for Bitcoin, which traded above $71,000 earlier this month. But in a somewhat surprise turn, the popular cryptocurrency, and the wider crypto market, have largely cooled. In recent weeks, it has continued to steadily decline. Bitcoin dropped below $66,000 last week, extending declines from a dip the prior week brought about by the latest Consumer Price Index data and the Federal Reserves interest rate decision.

Despite the short-term volatility, Bitcoin is up 38% this year.

Uncertainty over monetary policy has been driving much of the volatility around Bitcoin and other altcoins. While annual inflation has slowed to 3.3% year-over-year, it has remained well above the Feds 2% target. Given stubbornly high prices, Fed officials decided earlier this month to keep the benchmark federal funds rate steady between 5.25% and 5.5%, forecasting just one rate cut in 2024.

Its not just Bitcoin. Ether, the second-largest cryptocurrency by market capitalization, also fell 5% on Monday morning, coming in at around $3,320. Other major cryptocurrencies, including Solana, Dogecoin, and Cardano, all saw declines between 4% and 6%.

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Softbank CEO Says AI That’s 10000X Smarter Than Humans Is Inevitable – Hot Hardware

Softbank CEO Masayoshi Son remarked, during a shareholders meeting, that he believes AI will be 10,000 times smarter than human intelligence 10 years from now. Son also remarked that he saw Softbanks mission to be the evolution of humanity, while also stating he had finally discovered his own purpose in life.

During the meeting last week, Son remarked that the company will place its entire focus on pairing robots with artificial intelligence to be utilized in all sorts of mass production, logistics, and autonomous driving. Son recognized that the effort will require immense capital and pooling funds with partners, as he said Softbank could not finance it on its own.

Son began his speech talking about artificial general intelligence, or AGI. He added that he believes AI will be at least 10 times smarter than humans within 3-5 years, even earlier than he anticipated. However, he went on to say that if AGI is not going to be that much smarter than humans, then we dont need to change the way of living, we dont need to change the structure of human lifestyle.

Son, and Softbank have not had the best of years in the recent past. While some of Sons investments had good returns, there were also many that did not, such as office sharing company WeWork. However, Softbank subsidiary Arm, a British chip designer, has prospered in more recent times with the attention of investors focused on anything AI. It is perhaps of Arm that Son is now willing to make such a bold statement in terms of Softbanks mission, and his own vision.

During his speech, Son summed up his vision for himself and Softbank, remarking, Softbank was founded for what purpose? For what purpose was Masa Son born? It may sound strange, but I think I was born to realize ASI. He concluded, I am super serious about it.

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Correction in the cryptocurrency market: sign of trouble ahead? – Kitco NEWS

It seems to have become a trend that once journalists start focusing on a pattern in the financial market, it stops working. The same has happened with cryptocurrencies.

In mid-May, it was reported that the 90-day correlation coefficient between Bitcoin and the tech-heavy Nasdaq 100 index reached 0.46, the highest level since late August.

However, over the past week, while the index of major tech companies grew by more than 4.4%, theBTCUSD declined by 0.95%.

This begs the question: what is causing the loss of correlation, and how long will it last?

The decoupling started before the FOMC rate meeting and intensified after Jerome Powell's speech, in which the Fed chairman again made hawkish comments.

Specifically, he said that recent data indicate "some easing" of inflationary pressures but not yet enough to start easing monetary policy.

The main surprise was that the Fed's updated forecast calls for one rate cut in 2024, down from three cuts in March, as the labor market remains strong and the economy resilient.

Where did the money go if not into cryptocurrencies?

Although the regulator's signal could have been more encouraging, investor enthusiasm for the stock market, especially for technology stocks, has remained strong.

Apple's WWDC presentation also contributed, and investors reacted positively, albeit belatedly. The rise in stock prices began the day after the AI product announcement.

Small-cap stocks represented by the Russell 2000 index also remained subdued, along with the cryptocurrency market. The index still sits nearly 18% below its all-time high of 2021.

What's next?

In the case of the stock market, strategists at Goldman Sachs Group have raised their year-endforecast for the S&P 500 index to 5,600 points from the previous 5,200.

They justified their decision to upgrade forecasts for the third time in less than a year with a lower-than-average level of negative earnings and a higher price/earnings ratio.

However, for that to happen, inflation data must continue on a downward path, and the economy must show no signs of slipping into negative growth territory.

Will cryptocurrencies follow the same path?

For now, all available investor funds seem to flow into the "Magnificent 7", leaving little room for digital assets. Even the recent low trading volumes have not helped.

However, many experts maintain a positive outlook, especially for Bitcoin, forecasting targets above $100,000. Some even expect $1 million per coin.

Approach these outlooks with caution. Robert Kiyosaki is also known for his consistent optimism about Bitcoin going "to the moon," but we're still waiting for that to happen...

Disclaimer:The views expressed in this article are those of the author and may not reflect those of Kitco Metals Inc. The author has made every effort to ensure accuracy of information provided; however, neither Kitco Metals Inc. nor the author can guarantee such accuracy. This article is strictly for informational purposes only. It is not a solicitation to make any exchange in commodities, securities or other financial instruments. Kitco Metals Inc. and the author of this article do not accept culpability for losses and/ or damages arising from the use of this publication.

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Crypto stocks lower across the board as Bitcoin slides By Investing.com – Investing.com

Shares of cryptocurrency stocks are on the decline premarket Monday as the price of Bitcoin has declined more than 4% in the past 24 hours.

The leading cryptocurrency is currently trading at $61,159.6. Over the last seven days, Bitcoin has declined by almost 7%.

The Bitcoin price fell on Monday, extending a deep decline from the past week. Concerns over U.S. interest rates and anticipation of key inflation data have kept traders largely biased toward the dollar.

Traders have grown skeptical over the timing of the Federal Reserve's interest rate cuts. High rates are negative for crypto as they diminish the appeal of speculative, risk-driven assets.

As a result, Coinbase is trading -3.9% premarket, Marathon Digital Holdings (NASDAQ:) is at -5%, Riot Platforms (NASDAQ:) -3.3%, Hut 8 Mining Corp (HUT) -5.6%, CleanSpark (NASDAQ:) -4.5%, Microstrategy, Inc. (NASDAQ:) -5.1%, Cipher Mining (NASDAQ:) -6.3%, and Bitdeer Technologies (BTDR) -4%.

Broader cryptocurrency prices were also pressured on Monday.

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