#nvidia income

[reportwire]

Nvidia CEO praises ‘through the roof’ use of firm’s A.I. services—and investors seem to agree

Nvidia shares jumped in after-hours trading Wednesday, as the chipmaker beat expectations on revenue and said it was benefitting from a growing boom inA.I. technology driven by chatbots like OpenAI’s ChatGPT. The U.S.-based chip company’s revenues fell, as it reported $6.1 billion in revenue in the most recent quarter, a 21% fall from what it reported a year ago. (That revenue, at $7.6 billion,…

[kc22invesmentsblog]

The AI Revolution: Exploring AI Stocks and Their Potential for the Future

Written by Delvin Artificial Intelligence (AI) has emerged as a transformative force, revolutionizing industries and shaping the future of technology. As AI continues to gain momentum, investing in AI stocks presents an opportunity to participate in this technological revolution and potentially reap significant benefits. In this blog post, we will discuss the impact of AI on the future and delve…

[mostlysignssomeportents]

“Humans in the loop” must detect the hardest-to-spot errors, at superhuman speed

I'm touring my new, nationally bestselling novel The Bezzle! Catch me SATURDAY (Apr 27) in MARIN COUNTY, then Winnipeg (May 2), Calgary (May 3), Vancouver (May 4), and beyond!

If AI has a future (a big if), it will have to be economically viable. An industry can't spend 1,700% more on Nvidia chips than it earns indefinitely – not even with Nvidia being a principle investor in its largest customers:

https://news.ycombinator.com/item?id=39883571

A company that pays 0.36-1 cents/query for electricity and (scarce, fresh) water can't indefinitely give those queries away by the millions to people who are expected to revise those queries dozens of times before eliciting the perfect botshit rendition of "instructions for removing a grilled cheese sandwich from a VCR in the style of the King James Bible":

https://www.semianalysis.com/p/the-inference-cost-of-search-disruption

Eventually, the industry will have to uncover some mix of applications that will cover its operating costs, if only to keep the lights on in the face of investor disillusionment (this isn't optional – investor disillusionment is an inevitable part of every bubble).

Now, there are lots of low-stakes applications for AI that can run just fine on the current AI technology, despite its many – and seemingly inescapable - errors ("hallucinations"). People who use AI to generate illustrations of their D&D characters engaged in epic adventures from their previous gaming session don't care about the odd extra finger. If the chatbot powering a tourist's automatic text-to-translation-to-speech phone tool gets a few words wrong, it's still much better than the alternative of speaking slowly and loudly in your own language while making emphatic hand-gestures.

There are lots of these applications, and many of the people who benefit from them would doubtless pay something for them. The problem – from an AI company's perspective – is that these aren't just low-stakes, they're also low-value. Their users would pay something for them, but not very much.

For AI to keep its servers on through the coming trough of disillusionment, it will have to locate high-value applications, too. Economically speaking, the function of low-value applications is to soak up excess capacity and produce value at the margins after the high-value applications pay the bills. Low-value applications are a side-dish, like the coach seats on an airplane whose total operating expenses are paid by the business class passengers up front. Without the principle income from high-value applications, the servers shut down, and the low-value applications disappear:

https://locusmag.com/2023/12/commentary-cory-doctorow-what-kind-of-bubble-is-ai/

Now, there are lots of high-value applications the AI industry has identified for its products. Broadly speaking, these high-value applications share the same problem: they are all high-stakes, which means they are very sensitive to errors. Mistakes made by apps that produce code, drive cars, or identify cancerous masses on chest X-rays are extremely consequential.

Some businesses may be insensitive to those consequences. Air Canada replaced its human customer service staff with chatbots that just lied to passengers, stealing hundreds of dollars from them in the process. But the process for getting your money back after you are defrauded by Air Canada's chatbot is so onerous that only one passenger has bothered to go through it, spending ten weeks exhausting all of Air Canada's internal review mechanisms before fighting his case for weeks more at the regulator:

https://bc.ctvnews.ca/air-canada-s-chatbot-gave-a-b-c-man-the-wrong-information-now-the-airline-has-to-pay-for-the-mistake-1.6769454

There's never just one ant. If this guy was defrauded by an AC chatbot, so were hundreds or thousands of other fliers. Air Canada doesn't have to pay them back. Air Canada is tacitly asserting that, as the country's flagship carrier and near-monopolist, it is too big to fail and too big to jail, which means it's too big to care.

Air Canada shows that for some business customers, AI doesn't need to be able to do a worker's job in order to be a smart purchase: a chatbot can replace a worker, fail to their worker's job, and still save the company money on balance.

I can't predict whether the world's sociopathic monopolists are numerous and powerful enough to keep the lights on for AI companies through leases for automation systems that let them commit consequence-free free fraud by replacing workers with chatbots that serve as moral crumple-zones for furious customers:

https://www.sciencedirect.com/science/article/abs/pii/S0747563219304029

But even stipulating that this is sufficient, it's intrinsically unstable. Anything that can't go on forever eventually stops, and the mass replacement of humans with high-speed fraud software seems likely to stoke the already blazing furnace of modern antitrust:

https://www.eff.org/de/deeplinks/2021/08/party-its-1979-og-antitrust-back-baby

Of course, the AI companies have their own answer to this conundrum. A high-stakes/high-value customer can still fire workers and replace them with AI – they just need to hire fewer, cheaper workers to supervise the AI and monitor it for "hallucinations." This is called the "human in the loop" solution.

The human in the loop story has some glaring holes. From a worker's perspective, serving as the human in the loop in a scheme that cuts wage bills through AI is a nightmare – the worst possible kind of automation.

Let's pause for a little detour through automation theory here. Automation can augment a worker. We can call this a "centaur" – the worker offloads a repetitive task, or one that requires a high degree of vigilance, or (worst of all) both. They're a human head on a robot body (hence "centaur"). Think of the sensor/vision system in your car that beeps if you activate your turn-signal while a car is in your blind spot. You're in charge, but you're getting a second opinion from the robot.

Likewise, consider an AI tool that double-checks a radiologist's diagnosis of your chest X-ray and suggests a second look when its assessment doesn't match the radiologist's. Again, the human is in charge, but the robot is serving as a backstop and helpmeet, using its inexhaustible robotic vigilance to augment human skill.

That's centaurs. They're the good automation. Then there's the bad automation: the reverse-centaur, when the human is used to augment the robot.

Amazon warehouse pickers stand in one place while robotic shelving units trundle up to them at speed; then, the haptic bracelets shackled around their wrists buzz at them, directing them pick up specific items and move them to a basket, while a third automation system penalizes them for taking toilet breaks or even just walking around and shaking out their limbs to avoid a repetitive strain injury. This is a robotic head using a human body – and destroying it in the process.

An AI-assisted radiologist processes fewer chest X-rays every day, costing their employer more, on top of the cost of the AI. That's not what AI companies are selling. They're offering hospitals the power to create reverse centaurs: radiologist-assisted AIs. That's what "human in the loop" means.

This is a problem for workers, but it's also a problem for their bosses (assuming those bosses actually care about correcting AI hallucinations, rather than providing a figleaf that lets them commit fraud or kill people and shift the blame to an unpunishable AI).

Humans are good at a lot of things, but they're not good at eternal, perfect vigilance. Writing code is hard, but performing code-review (where you check someone else's code for errors) is much harder – and it gets even harder if the code you're reviewing is usually fine, because this requires that you maintain your vigilance for something that only occurs at rare and unpredictable intervals:

https://twitter.com/qntm/status/1773779967521780169

But for a coding shop to make the cost of an AI pencil out, the human in the loop needs to be able to process a lot of AI-generated code. Replacing a human with an AI doesn't produce any savings if you need to hire two more humans to take turns doing close reads of the AI's code.

This is the fatal flaw in robo-taxi schemes. The "human in the loop" who is supposed to keep the murderbot from smashing into other cars, steering into oncoming traffic, or running down pedestrians isn't a driver, they're a driving instructor. This is a much harder job than being a driver, even when the student driver you're monitoring is a human, making human mistakes at human speed. It's even harder when the student driver is a robot, making errors at computer speed:

https://pluralistic.net/2024/04/01/human-in-the-loop/#monkey-in-the-middle

This is why the doomed robo-taxi company Cruise had to deploy 1.5 skilled, high-paid human monitors to oversee each of its murderbots, while traditional taxis operate at a fraction of the cost with a single, precaratized, low-paid human driver:

https://pluralistic.net/2024/01/11/robots-stole-my-jerb/#computer-says-no

The vigilance problem is pretty fatal for the human-in-the-loop gambit, but there's another problem that is, if anything, even more fatal: the kinds of errors that AIs make.

Foundationally, AI is applied statistics. An AI company trains its AI by feeding it a lot of data about the real world. The program processes this data, looking for statistical correlations in that data, and makes a model of the world based on those correlations. A chatbot is a next-word-guessing program, and an AI "art" generator is a next-pixel-guessing program. They're drawing on billions of documents to find the most statistically likely way of finishing a sentence or a line of pixels in a bitmap:

https://dl.acm.org/doi/10.1145/3442188.3445922

This means that AI doesn't just make errors – it makes subtle errors, the kinds of errors that are the hardest for a human in the loop to spot, because they are the most statistically probable ways of being wrong. Sure, we notice the gross errors in AI output, like confidently claiming that a living human is dead:

https://www.tomsguide.com/opinion/according-to-chatgpt-im-dead

But the most common errors that AIs make are the ones we don't notice, because they're perfectly camouflaged as the truth. Think of the recurring AI programming error that inserts a call to a nonexistent library called "huggingface-cli," which is what the library would be called if developers reliably followed naming conventions. But due to a human inconsistency, the real library has a slightly different name. The fact that AIs repeatedly inserted references to the nonexistent library opened up a vulnerability – a security researcher created a (inert) malicious library with that name and tricked numerous companies into compiling it into their code because their human reviewers missed the chatbot's (statistically indistinguishable from the the truth) lie:

https://www.theregister.com/2024/03/28/ai_bots_hallucinate_software_packages/

For a driving instructor or a code reviewer overseeing a human subject, the majority of errors are comparatively easy to spot, because they're the kinds of errors that lead to inconsistent library naming – places where a human behaved erratically or irregularly. But when reality is irregular or erratic, the AI will make errors by presuming that things are statistically normal.

These are the hardest kinds of errors to spot. They couldn't be harder for a human to detect if they were specifically designed to go undetected. The human in the loop isn't just being asked to spot mistakes – they're being actively deceived. The AI isn't merely wrong, it's constructing a subtle "what's wrong with this picture"-style puzzle. Not just one such puzzle, either: millions of them, at speed, which must be solved by the human in the loop, who must remain perfectly vigilant for things that are, by definition, almost totally unnoticeable.

This is a special new torment for reverse centaurs – and a significant problem for AI companies hoping to accumulate and keep enough high-value, high-stakes customers on their books to weather the coming trough of disillusionment.

This is pretty grim, but it gets grimmer. AI companies have argued that they have a third line of business, a way to make money for their customers beyond automation's gifts to their payrolls: they claim that they can perform difficult scientific tasks at superhuman speed, producing billion-dollar insights (new materials, new drugs, new proteins) at unimaginable speed.

However, these claims – credulously amplified by the non-technical press – keep on shattering when they are tested by experts who understand the esoteric domains in which AI is said to have an unbeatable advantage. For example, Google claimed that its Deepmind AI had discovered "millions of new materials," "equivalent to nearly 800 years’ worth of knowledge," constituting "an order-of-magnitude expansion in stable materials known to humanity":

https://deepmind.google/discover/blog/millions-of-new-materials-discovered-with-deep-learning/

It was a hoax. When independent material scientists reviewed representative samples of these "new materials," they concluded that "no new materials have been discovered" and that not one of these materials was "credible, useful and novel":

https://www.404media.co/google-says-it-discovered-millions-of-new-materials-with-ai-human-researchers/

As Brian Merchant writes, AI claims are eerily similar to "smoke and mirrors" – the dazzling reality-distortion field thrown up by 17th century magic lantern technology, which millions of people ascribed wild capabilities to, thanks to the outlandish claims of the technology's promoters:

https://www.bloodinthemachine.com/p/ai-really-is-smoke-and-mirrors

The fact that we have a four-hundred-year-old name for this phenomenon, and yet we're still falling prey to it is frankly a little depressing. And, unlucky for us, it turns out that AI therapybots can't help us with this – rather, they're apt to literally convince us to kill ourselves:

https://www.vice.com/en/article/pkadgm/man-dies-by-suicide-after-talking-with-ai-chatbot-widow-says

If you'd like an essay-formatted version of this post to read or share, here's a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog:

https://pluralistic.net/2024/04/23/maximal-plausibility/#reverse-centaurs

Image: Cryteria (modified) https://commons.wikimedia.org/wiki/File:HAL9000.svg

CC BY 3.0 https://creativecommons.org/licenses/by/3.0/deed.en

[kawaiigals]

Title: A Tale of Transient Serenity The girl's gentle demeanor suggests a moment of calm and reflection. Clad in a crisp red and white school uniform, she stands poised on the serene shoreline where waves lap gently at her feet. Her gaze is lost amidst the distant horizon, perhaps contemplating the beauty of nature or simply taking a break from the rigors of daily life. With each incoming tide, it's as if time itself pauses, allowing us to appreciate the transient serenity she embodies. As the sun sinks into the ocean and casts long shadows across her form, one can almost hear the whispers of secrets held by this tranquil setting. It is a snapshot of a quiet interlude, where the world outside seems far away and all that matters is the moment captured in time. [AD] Powered by NVIDIA GPU

[datarep]

NVIDIA Income Statement Q1 FY2025

by u/giteam

[lyingbard]

Update: Patience Fans Winning Again (Import Poll Decisions Too!)

So I've got a version working with all the features for a solid beta, but... only on my computer.

It should work when I set it up with all the cloud nonsense it needs, but it costs money, I don't wanna spend money right now, and I can't really make you pay for a product I'm not sure will work right.

So here's the deal: I'm starting a paid internship soon, so once I have that income I'll be willing to spend money on this. Problem: it's a National Parks internship so I won't have internet or the computer that I make LyingBard with until I get back... in 3-6 months.

But! I also want to ask you an important question...

I've been making LyingBard as a Cloud-Based app. It allows you to use it from anywhere through my website, but it also means I incur the cost of finding GPUs to run this with while you have a perfectly good GPU sitting in your computer doing nothing (also cloud apps are a pain in the ass).

I could also make it a Desktop App, but it would be about 1GB (blame PyTorch), it would only run on NVIDIA GPUs, and you'd have to set up your own discord bots and stuff (although I can try and streamline that for you).

Another big problem is money. Cloud-Based stuff costs money to run and becomes basically a job even if it doesn't pay enough. I'm considering a career in the National Parks Service so I won't be available most of the time if something goes wrong and stuff can go VERY wrong with a paid cloud app (think leaked passwords, compromised payment processor (Stripe) account, that sort of thing).

A Desktop App, however, can be left alone without spontaneously deleting itself or attacking you, but I would certainly have to focus on a career unless you donated a whole heck of a lot.

So DECIDE TIME! After carefully (or carelessly, idc) considering these options. WHICH DO YOU CHOOSE?!

Unfortunately, LyingBard isn't releasing until I get back regardless. Even the desktop app is just a bit too much work for me to get done before I leave.

[govindhtech]

NVIDIA AI Workflows Detect False Credit Card Transactions

A Novel AI Workflow from NVIDIA Identifies False Credit Card Transactions.

The process, which is powered by the NVIDIA AI platform on AWS, may reduce risk and save money for financial services companies.

By 2026, global credit card transaction fraud is predicted to cause $43 billion in damages.

Using rapid data processing and sophisticated algorithms, a new fraud detection NVIDIA AI workflows on Amazon Web Services (AWS) will assist fight this growing pandemic by enhancing AI’s capacity to identify and stop credit card transaction fraud.

In contrast to conventional techniques, the process, which was introduced this week at the Money20/20 fintech conference, helps financial institutions spot minute trends and irregularities in transaction data by analyzing user behavior. This increases accuracy and lowers false positives.

Users may use the NVIDIA AI Enterprise software platform and NVIDIA GPU instances to expedite the transition of their fraud detection operations from conventional computation to accelerated compute.

Companies that use complete machine learning tools and methods may see an estimated 40% increase in the accuracy of fraud detection, which will help them find and stop criminals more quickly and lessen damage.

As a result, top financial institutions like Capital One and American Express have started using AI to develop exclusive solutions that improve client safety and reduce fraud.

With the help of NVIDIA AI, the new NVIDIA workflow speeds up data processing, model training, and inference while showcasing how these elements can be combined into a single, user-friendly software package.

The procedure, which is now geared for credit card transaction fraud, might be modified for use cases including money laundering, account takeover, and new account fraud.

Enhanced Processing for Fraud Identification

It is more crucial than ever for businesses in all sectors, including financial services, to use computational capacity that is economical and energy-efficient as AI models grow in complexity, size, and variety.

Conventional data science pipelines don’t have the compute acceleration needed to process the enormous amounts of data needed to combat fraud in the face of the industry’s continually increasing losses. Payment organizations may be able to save money and time on data processing by using NVIDIA RAPIDS Accelerator for Apache Spark.

Financial institutions are using NVIDIA’s AI and accelerated computing solutions to effectively handle massive datasets and provide real-time AI performance with intricate AI models.

The industry standard for detecting fraud has long been the use of gradient-boosted decision trees, a kind of machine learning technique that uses libraries like XGBoost.

Utilizing the NVIDIA RAPIDS suite of AI libraries, the new NVIDIA AI workflows for fraud detection improves XGBoost by adding graph neural network (GNN) embeddings as extra features to assist lower false positives.

In order to generate and train a model that can be coordinated with the NVIDIA Triton Inference Server and the NVIDIA Morpheus Runtime Core library for real-time inferencing, the GNN embeddings are fed into XGBoost.

All incoming data is safely inspected and categorized by the NVIDIA Morpheus framework, which also flags potentially suspicious behavior and tags it with patterns. The NVIDIA Triton Inference Server optimizes throughput, latency, and utilization while making it easier to infer all kinds of AI model deployments in production.

NVIDIA AI Enterprise provides Morpheus, RAPIDS, and Triton Inference Server.

Leading Financial Services Companies Use AI

AI is assisting in the fight against the growing trend of online or mobile fraud losses, which are being reported by several major financial institutions in North America.

American Express started using artificial intelligence (AI) to combat fraud in 2010. The company uses fraud detection algorithms to track all client transactions worldwide in real time, producing fraud determinations in a matter of milliseconds. American Express improved model accuracy by using a variety of sophisticated algorithms, one of which used the NVIDIA AI platform, therefore strengthening the organization’s capacity to combat fraud.

Large language models and generative AI are used by the European digital bank Bunq to assist in the detection of fraud and money laundering. With NVIDIA accelerated processing, its AI-powered transaction-monitoring system was able to train models at over 100 times quicker rates.

In March, BNY said that it was the first big bank to implement an NVIDIA DGX SuperPOD with DGX H100 systems. This would aid in the development of solutions that enable use cases such as fraud detection.

In order to improve their financial services apps and help protect their clients’ funds, identities, and digital accounts, systems integrators, software suppliers, and cloud service providers may now include the new NVIDIA AI workflows for fraud detection. NVIDIA Technical Blog post on enhancing fraud detection with GNNs and investigate the NVIDIA AI workflows for fraud detection.

Read more on Govindhtech.com

[newstfionline]

Friday, October 18, 2024

Big Tech Goes Nuclear (1440) Amazon is investing $500M toward nuclear power to meet the rising energy demands of its data centers and artificial intelligence initiatives. Yesterday’s announcement comes two days after Google unveiled plans to purchase nuclear power and less than a month after Microsoft said it would reopen the Three Mile Island plant—home to the worst nuclear accident in US history—to fuel its AI efforts. Nuclear power accounts for 19% of US electricity generation and comes from energy released when the nucleus of a heavy atom splits into lighter atoms. While expensive and potentially hazardous, proponents pitch nuclear power as a clean alternative to greenhouse gas-emitting energy sources like coal, oil, and gas. Energy-intensive generative AI applications and data centers are expected to account for roughly 9% of total US power consumption by 2030.

Many schools are still closed weeks after Hurricane Helene. Teachers worry about long-term impact (AP) Tens of thousands of students in the Southeast are dealing with school disruptions after Hurricane Helene wreaked havoc so severe—on homes, campuses and municipal power and water systems—that some districts have no idea when they will reopen. While virtual learning helped during the COVID-19 school closures, that has not been an option for this crisis because internet and cellphone service has remained spotty since the storm struck in late September. In hard-hit western North Carolina, some districts warn students will miss up to a month of school, and others say they can’t yet determine a timeline for returning to classrooms. “I feel like a month is a lot, but it’s not something that can’t be overcome,” said Marissa Coleman, who has sent her four children to stay with grandparents in Texas because their home in North Carolina’s Buncombe County has no running water. “But if we get further into Thanksgiving and Christmas, it’s like, how are they actually going to make this up?”

Anguilla has turned the AI boom into a digital gold mine (AP) The artificial intelligence boom has benefited chatbot makers, computer scientists and Nvidia investors. It’s also providing an unusual windfall for Anguilla, a tiny island in the Caribbean. The British territory was allotted control of the .ai internet address in the 1990s. It was one of hundreds of obscure top-level domains assigned to individual countries and territories based on their names. While the domains are supposed to indicate a website has a link to a particular region or language, it’s not always a requirement. Google uses google.ai to showcase its artificial intelligence services while Elon Musk uses x.ai as the homepage for his Grok AI chatbot. Startups like AI search engine Perplexity have also snapped up .ai web addresses. Anguilla’s earnings from web domain registration fees quadrupled last year to $32 million, fueled by the surging interest in AI. The income now accounts for about 20% of Anguilla’s total government revenue.

Is Brazil’s Supreme Court Saving Democracy or Threatening It? (NYT) Daniel Silveira, a policeman turned far-right Brazilian congressman, was furious. He believed Brazil’s Supreme Court was persecuting conservatives and silencing them on social media, and he wanted to do something about it. So he sat on his couch and began recording. “How many times have I imagined you getting beat up on the street,” he said in a 19-minute diatribe against the court’s justices. He posted the video on YouTube in February 2021, adding, “I’ll say what I want on here.” A Brazilian Supreme Court justice immediately ordered his arrest. A year later, 10 of the court’s 11 justices convicted and sentenced him to nearly nine years in prison for threatening them. Jair Bolsonaro, Brazil’s president at the time, pardoned Mr. Silveira, but the Supreme Court overruled him. Today, Mr. Silveira remains in prison. There is no room for appeal past the Supreme Court. Mr. Silveira’s case is part of a creeping institutional crisis for Brazil. For the past five years, the nation’s Supreme Court has expanded its power to carry out a sweeping campaign to protect Brazilian institutions from attacks, many of them online. To the Brazilian left, the offensive has helped rescue Brazil’s democracy. To the right, it has made the court a threat to democracy itself.

France's Macron calls for an end to arms exports used in Gaza and Lebanon (Reuters) Israeli Prime Minister Benjamin Netanyahu and French President Emmanuel Macron are getting into a mud-slinging fight for all the world to see. Last week, Macron called for an arms embargo on Israel, saying that the country needed to find a political solution to its issues in Gaza and Lebanon. Netanyahu responded with an angry video posted on X, calling Macron (and others calling for an arms embargo on Israel) a “disgrace.” On Tuesday (this week), Macron reportedly made statements during a closed-door meeting with French ministers, saying that Netanyahu should not “ignore United Nations decisions” because “his country was created by a U.N. decision.” Israel has repeatedly called for the dismantling of UNRWA, the UN agency that provides aid for Palestinian refugees, and is looking to pass legislation barring the organization from operating in Israeli territory—a decision the UNRWA warns will essentially “disintegrate” its services in Gaza and the West Bank. Israeli soldiers have also targeted U.N. peacekeepers in Lebanon on multiple occasions since the IDF’s ground invasion of the country began earlier this month. Netanyahu clapped back at Macron soon after his statements, saying, “It was not the U.N. resolution that established the State of Israel, but rather the victory achieved in the War of Independence with the blood of heroic fighters, many of whom were Holocaust survivors—including from the Vichy regime in France.”

Zelenskyy outlines his ‘victory plan’ to Ukraine’s lawmakers (Politico) Yesterday, Ukrainian President Volodymyr Zelenskyy unveiled his grand “victory plan” to Ukraine’s parliament. It’s made up of five main points and three secret annexes—we’re not privy to the annexes, but here are the five main points: an invitation to join NATO, a larger and faster supply of Western weapons with no restrictions on their use, a non-nuclear strategic deterrence package, deals which would trade Ukraine’s energy resources for money up front, and the possibility of U.S. forces training with battle-hardened Ukrainian forces after the war. Kyiv’s Western allies have not met the plan with the enthusiasm Ukraine might have been expecting. Meanwhile, Russia is getting a new infusion of troops. According to a senior Ukrainian military intelligence official, Russia has gathered over 3,000 North Koreans to fight in Ukraine. Russia disputes this and it’s unconfirmed.

Monsoon flooding closes schools and offices in India’s southern IT hubs (AP) Schools, colleges and government offices were shut Wednesday in parts of southern India as heavy monsoon rains triggered severe flooding. The worst-hit cities included Chennai and Bengaluru, the country’s industrial and information technology hubs. Power cuts and flight cancellations caused disruption, and thousands of residents prepared for more downpours over the next 48 hours. The June-September monsoon season has receded in northern parts of the country. However, the northeast monsoon has brought heavy rains to coastal Andhra Pradesh, Tamil Nadu, Kerala, and southern Karnataka state. At least 33 people died last month in rains and floods.

For Working Women in India, Staying Safe Can Feel Like a Full-Time Job (WSJ) When Ajita Topo, a cook in an affluent neighborhood in Delhi, leaves work in the evening, she holds her bag like a shield against her chest, keeps her fists clenched and carries a black umbrella with a very sharp end to ward off a possible attack. She makes sure to wear lots of layers—no matter how hot it is—to deter someone from trying to grope her chest, and secures her bun with a sharp metal stick as an additional weapon. Topo isn’t being paranoid. Last year, she was followed by two men when she left work after 10 p.m. She managed to scare them away by shouting as she passed homes with guards outside. “Workplace, public transport, public places, we feel safe nowhere,” said Topo, the sole breadwinner for her two children. “The only solution is to stay alert at all times.” For many women in India, taking steps to ward off a violent attack—and reassuring their families they are safe while at work and on their commutes—is an invisible form of labor that is a central element of their work life. The killing and rape of a trainee doctor in the city of Kolkata in August was a fresh reminder for Indian women who work of the dangers lurking in public spaces where women are far less visible than men.

Where a Million Desperate People Are Finding Shelter in Lebanon (NYT) At dusk, the parking lot of Tripoli’s Quality Inn is packed with cars and families milling about. Children’s shouts fill the air, reminding some of better times, when the hotel hosted weddings and birthdays parties. Now, though, the cars in the lot are dusty and battered, the families sit on patches of grass, their faces worn with worry, and the children play in a drained swimming pool. That is because the Quality Inn has been transformed into one of the biggest shelters in Tripoli for displaced Lebanese fleeing Israeli bombing in the country’s south. In Lebanon, the displaced are practically everywhere. In Beirut, the capital, where many are staying, they have set up makeshift tents on the corniche by the sea, crafting shelters out of stray metal poles, bits of awnings and blankets. In the city’s parks and squares, some families have placed floor coverings on the ground, anchoring them with cases of water and folded blankets. Others are taking shelter anywhere that they can, mostly in schools but also in unfinished buildings. Of a population of around six million, including about two million Syrian refugees, just over one million people have been forced from their homes by the bombings, the United Nations and the Lebanese authorities say.

IDF says it killed top Hamas leader (Politico) The Israel Defense Force confirmed it has killed top Hamas leader Yahya Sinwar, the lead architect of the Oct. 7 attack and the No. 1 target of its yearlong campaign in Gaza. Details of Sinwar’s death remain sketchy, but he appears to have been killed in an operation in southern Gaza that was not specifically targeting him. It is unclear what effect, if any, Sinwar’s death will have on the future of Israel’s campaign in Gaza, let alone on the newly emerging front against Hezbollah in Lebanon.

Israeli attacks on aid convoys in Gaza persist, U.N. says (Washington Post) Israeli troops have opened fire on U.N. aid convoys to northern Gaza at least four times in three months, according to U.N. and other humanitarian officials, damaging the vehicles and narrowly missing staff members inside. On Sept. 9, the officials said, the Israeli army held a convoy involved in the United Nations’ polio response at gunpoint for 7½ hours, claiming that several people in the vehicles were wanted men. They were questioned and eventually allowed to proceed. “They basically surrounded our vehicles, pointing assault rifles at our cars, and they were shouting that we’re terrorists,” said one U.N. staffer. U.N. officials describe the Sept. 9 incident as emblematic of an environment of mistrust, in which Israeli soldiers, many of them reservists, command significant power at the checkpoints that humanitarian workers must cross to enter northern Gaza and face few consequences for their actions.

Why Big Pharma refuses to take on the threat of antibiotic-resistant germs (Die Zeit/Germany) Some 40 million people will die from antibiotic-resistant germs in the next 25 years, according to the latest estimate. All reasonable experts agree: New medicines must be developed urgently, otherwise we will face the threat of living in a post-antibiotic era, an era in which people die from simple infections because doctors can no longer treat them. Yet although the problem and solutions are obvious, there are very few new antibiotics in the research pipelines of the big pharmaceutical companies. More and more companies are even closing down their antibiotics divisions. The reason? Antibiotics are not profitable. Poor countries are not lucrative sales markets. Companies would rather focus on another cancer drug that marginally improves the prognosis for lung cancer; another cholesterol-lowering drug that is slightly more effective than its predecessor and is so inexpensive to develop that it brings in billions without any major risks; or yet another anticoagulant. And so billions of dollars in development costs are spent on drugs that have little impact on people’s health, while virtually nothing is spent on developing drugs that could save millions of lives.

[sideburnguru]

My hot take on the AI vs creativity debate. For context I'm a filmmaker and mess around with all creative aspects of bringing something to the screen.

It's the same argument with automation. Growing up in the 2010's you couldn't go long without being asked to consider whether robots replacing human jobs was ethical or not. Short answer was no, since it's replacing unskilled labour and would lead to millions of people around the world losing their income. But back then the jobs in question were specifically unskilled labour, something NON INTELLIGENT.

The first wave of AI being creative as I remember it was the shitty generation of landscapes and around 2020 ish. Same thing as today where it would create images based off of prompts, but it was really shitty and would only barely resemble what you had in mind, and couldn't even do anything specific. It was closer to a gimmick than anything.

The second wave in my memory was when Nvidia and a bunch of companies made software that could generate landscapes based off of prompts or some unique software with brushes and stuff. The stuff was, all things considered, usable and decent looking.

And the third wave is what happened as soon as chatGPT came into existence, and the modern debate. The weird thing is that (as far as I remember) people weren't raising hell during the first two waves. It was only until after the art became good and the technology became able to understand more advanced prompts did we complain. We recycled the arguments from automation because it was essentially the same thing, but now there was an argument that AI art has "no soul".

That last argument really stands out, because I genuinely don't believe a majority of people have what I consider a soul, not even creatives. I think it's something that has to by the individual through discovering and defining their meaning of life. Yet, even the soulless are asking for AI to be limited or stopped being developed because it may stifle their creativity or employment prospects.

How I see it? Knowing that it could very well prevent me from being able to make a living from doing the thing I've decided to dedicate my life to? I say bring it on. I think this is the defining struggle of creatives of our generation, to be able to prove their worth against frankly superior soulless artists.

Want to be employed for being creative? If you can't beat AI then you probably weren't going to make it too far anyways.

Want to express creativity for yourself? No one's stopping you, create your magnum opus.

I know about AI being trained on existing artists art and how it's going to just further the evil capitalist machine but as it is this is where I stand.

[abbiistabbii]

Fun fact, Nvidia is the richest company in the world right now because scalpers and crypto-bros bought up all their GPUs for Cryptomining but they're reluctant to admit this in front of investors because they know how fucking lame that sounds.

Their Chief Tech officer said they offer nothing to society despite basically becoming the richest company because of everyone buying their shit for crypto farming. It's like a great Shakespearean actor who's known as a master of his craft cringing knowing that most of his income comes from his role as "Mr Fartsy" from the TV show "Poo Poo Pee Pee fun time."

[skrillnetworkblog]

📈 US Stock Market: Cautious Optimism Meets Strategic Focus

🔍 Key Highlights:

1️⃣ Mixed Market Moves:

Dow Jones: Slight drop of -61.63 points (-0.15%) reflects investor caution.

S&P 500: Marginal decline (-0.069%) signals a "pause-and-watch" sentiment.

Nasdaq Composite: Modest gain (+0.062%), led by tech resilience and growth optimism.

2️⃣ Treasury Yields Spike:

10-Year Treasury Yield: Climbs to 4.445% amid inflation concerns, signaling expectations of higher interest rates.

3️⃣ Fed Watch:

Market participants await the FOMC minutes for clarity on rate decisions.

Fed officials urge patience, citing a need for improved inflation data before considering rate cuts.

4️⃣ Nvidia Earnings Spotlight:

AI and GPU giant Nvidia (NVDA) to release earnings, a key focus for tech investors.

Analysts eye updates on AI spending and market expansion.

5️⃣ Corporate Earnings Context:

Mixed performance from companies like Target reflects consumer behavior trends and economic health.

6️⃣ Nasdaq Bull Run:

From 15,500 points (Apr 22, 2024) to 16,833 points, the Nasdaq shows robust tech-driven growth.

📊 Investor Takeaways:

Stay informed with economic indicators and corporate earnings updates.

Diversify portfolios to balance risks across sectors like technology, consumer goods, and fixed income.

Focus on long-term growth areas, including AI, technology, and renewable energy.

💡 Strategy Insights:

Leverage short-term fluctuations to strengthen long-term positions.

Use FOMC insights and Nvidia’s results to shape informed investment strategies.

🚀 Stay ahead in the market by keeping a sharp eye on pivotal updates and embracing diversification to manage risks while seizing growth opportunities!

Visit - https://www.skrillnetwork.com/key-fed-minutes-and-nvidia-earnings-shape-us-stock-market-moves

[isfeed]

Nvidia’s CEO defends his moat as AI labs change how they improve their AI models

Nvidia raked in more than $19 billion in net income during the last quarter, the company reported on Wednesday, but that did little to assure investors that its rapid growth would continue. On its earnings call, analysts prodded CEO Jensen Huang about how Nvidia would fare if tech companies start using new methods to improve […] © 2024 TechCrunch. All rights reserved. For personal use…

[accapitalmarket]

Near-term rate cuts kept Wall Street afloat, crude oil retreats

US blue chips ended higher on Thursday, rallying late on amid Federal Reserve rate cut hopes, though tech issues took a tumble on caution ahead of earnings from the world’s biggest company, AI chipmaker Nvidia.

Investors were parsing speeches from Fed members on the prospects for further rate cuts. Federal Reserve Governor Lisa Cook said that future cuts would be dependent on incoming economic data. Meanwhile, Federal Reserve governor Michelle Bowman backed a cautious approach to rate cuts amid expectations that the neutral level or end point for rates may be higher than previously expected given that inflation has stalled in recent months.

Investors, however, continue to bet that US interest rates will fall in the near-term, with traders pricing in a 60.6% chance for a 25-basis point cut by the Federal Reserve in December

At the close in New York, the blue-chip Dow Jones Industrials Average was up 0.30% at 43,408, while the broader the S&P 500 index ended flat at 5,917, with both having rallied late on from earlier losses.

US30 Daily

But the tech-laden Nasdaq Composite remained weak, though it also ended well off session lows, down 0.1%, at 18,966.

SPX500 H1

AI leader Nvidia, which has nearly tripled in value this year, fell 1.1% ahead of its results that were released after the closing bell. The stock dropped another 2.9% after-hours despite the chipmaker delivering third quarter revenue and profits above estimates and better-than-expected revenue guidance for the December quarter, with the figures not a complete blow-out.

Among other weak tech stocks in the session, Alphabet shed 1.3%, while Microsoft fell 1.6%, and Amazon.com lost 0.9%.

But Netflix sidestepped the weakness, adding 1.4% after announcing that last week's boxing bout between YouTube star Jake Paul and former world heavyweight champion Mike Tyson racked up 108 million global viewers, becoming the most-streamed global sporting ever.

And cryptocurrency stocks ticked higher as bitcoin reached a record high above $94,000, with MicroStrategy jumping 10.1% and MARA Holdings up 14.0%.

Away from tech, Target was the biggest casualty, plunging 21.4% after the retailer forecast holiday-quarter comparable sales and profit below Wall Street expectations following a third-quarter estimate miss.

The earnings missed triggered a sell-off by other retailers, with Home Depot down 1.7%.

But fellow home goods retailer Williams-Sonoma surged 27.5%, hitting a new all-time high, after boosting its full-year sales outlook and reporting a Q3 earnings beat.

Red Cat jumped 34.4% after the drone technology firm was selected by the US Army as the production provider for its Short Range Reconnaissance (SRR) Program of Record.

Among commodities, oil prices were lower as US crude stocks rose by more than expected last week, although the losses were capped by worries about the intensifying war between major oil producer Russia and Ukraine.

USOIL Daily

UK Brent Crude was down 0.3%, at $73.11, a barrel, while US West Texas Intermediate crude fell 0.6% to $68.95 a barrel.

Meanwhile, analysts at broker Macquarie forecast that oil prices are shaping up to test new lows next year as the market appears to be pricing in a large crude surplus at a time when the demand outlook looks bleak.

Disclaimer: The information contained in this market commentary is of general nature only and does not take into account your objectives, financial situation or needs. You are strongly recommended to seek independent financial advice before making any investment decisions. Trading margin forex and CFDs carries a high level of risk and may not be suitable for all investors. Investors could experience losses in excess of total deposits. You do not have ownership of the underlying assets. AC Capital Market (V) Ltd is the product issuer and distributor. Please read and consider our Product Disclosure Statement and Terms and Conditions, and fully understand the risks involved before deciding to acquire any of the financial products provided by us. The content of this market commentary is owned by AC Capital Market (V) Ltd. Any illegal reproduction of this content will result in immediate legal action.

[igettalk]

Nvidia has recorded a great third quarter profit as against what was expected for both sales and benefits, while they provide a good-looking forecast for the current quarter. The Nvidia team is expecting a sum of $37.5 billion in income, which is a little bigger than $37.08 billion that analyst had estimated. Growth is not that good compared to the enticing 265% seen in periods before, despite a 94% year-over-year income surge in the quarter that ended on the 27th of October. The company is doing great in terms of AI dominance, with its data center being responsible for almost all of the revenue. There was a report of $30.8 billion in sales as reported by division, a 112% increase in 2023 that defeated $28.82 billion that was expected. Almost $3.1 billion of this revenue is from networking components. Nvidia's AI chips, which include the next-generation Blackwell, are currently being demanded by customers, with 13,000 simples already with clients like OpenAI and Microsoft. Nvidia has aimed for several billion dollars in Blackwell revenue for the fourth quarter as shipments move in 2025. The gaming part of the company did not perform badly either, generating $3.28 billion, which is caused by the rise in GPU's demand for game consoles and PCs. The automotive sector also increased by 72%, reaching $449 million courtesy of self-driving car technologies. Nvidia's stronghold in AI is the reason for the robust growth trajectory despite extended trading that witnessed a 2% share loss. Read the full article

[seriously-mike]

Working Awkward Bass

Well, kids, more AI bullshit incoming. This time, we'll be looking at an open-source project called PaintsUndo: it's supposed to generate a work-in-progress video of the supposed creation of your AI-generated image. And I wouldn't be myself if I didn't go and turn it inside out.

You know this one. I drew it long ago, by hand, based on a photo I found on DeviantArt. Not the finest piece of art, but it's mine. Now, let's try and see what keyframes for the "work in progress" video PaintsUndo created:

Hold on, stop, what the fuck. Why is it anime? I can't draw anime for shit, I don't even particularly like anime, and here you're starting off with something that doesn't even look like the drawing in question?!

I mean, look at the first one. We're dealing with a shot that's framed slightly below the waist at its lowest point and for some reason the faked WIP video starts with a knees-up 3/4 shot that has nothing to do with the end result and gets redrawn into the waist-up frontal shot about a quarter of the way in? Why in the fuck would you even over-egg the custard like that?!

The second one is the "getting redrawn" stage. So the right hand and the weird roundish scribble around it are everything that's left from the 3/4 shot. Nonsense. That right hand will be erased anyway, so nobody cares, but still. Also, look at the hair. It's combed back. It's not parted to the sides like I drew it, there's not even a hint of the strand falling on Lex's face, it's a clear hint that there's a lot of bullshit going on here.

The third one is the "almost ready" stage. So fucking what that the tattoo designs that should be in place by then don't look like anything even barely adjacent to the final ones, it's not like anyone's gonna care, right? The video is going to be a jittery slideshow anyway.

And as for the video, um, well... The online version refuses to generate it, claiming that all available attempts were used up and I'll get new ones in -1 days. Which, in computer programmers' parlance means never. Like LOL, get fucked, you can get a bad image-to-prompt based on booru tags (and like I said, booru tags are for the mentally deficient), you can get a couple of "work in progress" sketches that don't make sense, but you're not getting a video. You can try running it on your PC, but, uh...

The inference is tested with 24GB VRAM on Nvidia 4090 and 3090TI. It may also work with 16GB VRAM, but does not work with 8GB. My estimation is that, under extreme optimization (including weight offloading and sliced attention), the theoretical minimal VRAM requirement is about 10~12.5 GB.

MOTHERFUCKER WHAT. 24 GB of VRAM is fucking overkill for something that obviously runs on Stable Diffusion 1.5, and you're telling me that this is just a proof of concept that needs to be "optimized"? Get the fuck out with that bullshit.

[datarep]

NVIDIA Income Statement Q3 2023

by u/giteam