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Category: finance – Page 9

#GigaBerlinArt #TechPainters #RoboticMuralist.
At Tesla’s Gigafactory Berlin-Brandenburg, creativity meets technology in a remarkable initiative to transform concrete surfaces into stunning artworks. Inspired by Elon Musk’s vision to turn the factory into a canvas, the project began with local graffiti crews. However, the sheer scale of the endeavor required innovative solutions, leading to the collaboration with a robotic muralist startup. This groundbreaking graffiti printer combines cutting-edge technology with artistry, using a triangulation method to maneuver its print head along factory walls. With 12 paint cans onboard, the robot sprays precise dots of color—10 million per wall and 300 million for the west side alone—creating intricate designs composed of five distinct colors. The curated artworks draw inspiration from Berlin’s vibrant culture, Tesla’s groundbreaking products, and the factory itself—described as “the machine that builds the machine.” A blend of global and in-house artistic talent has contributed to the ongoing project, making Giga Berlin not just a hub for innovation but also a celebration of art and ingenuity.

Courtesy: X:@Tesla.

#FactoryArt #BerlinCulture #GigaBerlinTransformation #MachineThatBuildsTheMachine.

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In today’s AI news, OpenAI is announcing a new AI Agent designed to help people who do intensive knowledge work in areas like finance, science, policy, and engineering and need thorough, precise, and reliable research. It could also be useful for anyone making major purchases.

In what most would consider a halcyon time for AI, an anachronistic source has just added their two cents to the ethos around the AI revolution. The Vatican released a significant broadside addressing the potential and risks of AI in a new high-tech world. It’s a very interesting look at these new technologies, with a focus on human worth and human dignity.

In other advances, the one-person micro-enterprise is far from a novel concept. Cheap on-demand AI compute, remote collaboration, payment processing APIs, social media, and e-commerce marketplaces have all made it easier to “go it alone” as an entrepreneur. But what about scaling that business into something meatier — a one-person Unicorn.

And, this morning, Brussels announced plans to develop an open source AI model of its own, with $56 million in funding to do it. The investment will fund top researchers from a handful of companies and universities across EU countries as they develop a large language model that can work with the trading bloc’s 30 languages.

In videos, Lex Fridman speaks with Dylan Patel, Founder of SemiAnalysis, a semiconductor research and analysis company, and Nathan Lambert, a research scientist at Allen Institute for AI (Ai2) and author of an AI blog called Interconnects. They all discuss DeepSeek, China, OpenAI, NVIDIA, xAI, TSMC, Stargate, and AI Megaclusters.

Then we tune into the Big Technology podcast to hear how companies are actually deploying AI agents and what it takes to move beyond proof of concepts to real deployment. Antoine Shagoury, Chief Technology Officer of Kyndryl, an IBM spinoff, joins Alex Kantrowitz show to discuss the real-world implementation of AI in enterprise environments.

And, we take a tour of a fully automated e-commerce warehouse run by AI robots. Brightpick Autopicker is the only autonomous mobile robot (AMR) in the world that robotically picks and consolidates orders directly in the warehouse aisles, like a human with a cart.

Continue reading “OpenAI Unveils A New ChatGPT Agent For ‘Deep Research’ Analysis And Reporting” | >

Bloomberg on the Economic Singularity:

“If AI is about to get much cheaper, the path to an answer on its economic impact is going to get shorter. For workers nervously wondering if large language models will make their skills redundant, a lot is riding on which camp is right.”

For investors in artificial intelligence, the last week delivered a painful shock. The sudden appearance of DeepSeek — a Chinese AI firm boasting a world-class model developed at bargain-basement costs — triggered a massive selloff in Nvidia and other US tech champions.

What matters for the economy, though, is not the ups and downs of stock prices for the Magnificent Seven, but whether AI drives gains in productivity, and how those gains are divided up. For all the excitement, and the trillion-dollar valuations for AI firms, evidence of a boost to productivity remains thin on the ground.

Have a confidential tip for our reporters? Get in Touch.

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Shoeb Javed is chief product officer at iGrafx.

Navigating the intricacies of compliance and risk management can seem overwhelming for businesses, especially those operating in heavily regulated industries. The rules are complex and the stakes are high, and the old ways of managing compliance aren’t enough anymore. By using smart tools and clear processes, businesses can handle tasks more efficiently, reduce risks and make audits less stressful.

Many organizations face a daunting array of compliance requirements, both external and internal. Regulatory demands vary across industries such as financial services, healthcare, manufacturing, retail and technology. Businesses may also have to contend with regulations that differ by country and even by region.

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On the positive side, some human entrepreneurs could become very wealthy, possibly trillionaires if they could tap into these AI’s wealth somehow. Additionally, super rich AIs could be a solution to the United States’ growing debt crisis, and eliminate the need for whether countries like China can continue to buy our debt so we can indefinitely print dollars. In fact, can America launch its own AI agents to create enough crypto wealth to buy its debt?

Naturally, the risk is that these AIs might eventually try to buy other financial instruments, like existing bonds and stocks. But it’s unlikely they’d be able to do so, unless more of the U.S.’ economy went into crypto and became blockchain based. Additionally, AI bots aren’t allowed to have traditional bank accounts yet.

Whatever happens, clearly there is an urgent need for the U.S. government to address such potentialities. Given that these AIs could start to proliferate in the next few months, I suggest Congress and the Trump administration immediately convene a special task force to specifically tackle the possibility of an AI Monetary Hegemony.

The real danger is that even with regulation, programmers will still be able to release autonomous AIs into the wild—just as many illegal things already happen on the web despite the existence of laws. Programmers might release these types of AIs for kicks, while others try to profit from it—and some may even do so even as a form of terrorism to try to hamper the world economy. Whatever the reason, the creation of autonomous AIs will soon be a reality of life. And vigilance and foresight will be needed as these new AIs start to autonomously disrupt our financial future.

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Cybersecurity researchers are calling attention to a new malware campaign that leverages fake CAPTCHA verification checks to deliver the infamous Lumma information stealer.

“The campaign is global, with Netskope Threat Labs tracking victims targeted in Argentina, Colombia, the United States, the Philippines, and other countries around the world,” Leandro Fróes, senior threat research engineer at Netskope Threat Labs, said in a report shared with The Hacker News.

“The campaign also spans multiple industries, including healthcare, banking, and marketing, with the telecom industry having the highest number of organizations targeted.”

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In today’s AI news, a new $500 billion, private sector investment to build artificial intelligence infrastructure in the US, with Oracle, ChatGPT creator OpenAI, and Japanese conglomerate SoftBank among those committing to the project. The joint venture, called Stargate, is expected to begin with a data center project in Texas.

In other advancements, Perplexity has launched an aggressive bid to capture the enterprise AI search market, unveiling Sonar, an API service that outperforms offerings from Google, OpenAI and Anthropic on key benchmarks while also undercutting their prices. Perplexity — now valued at $9 billion — directly challenges larger competitors.

And, Santee Cooper, the big power provider in South Carolina, has tapped financial advisers to look for buyers that can restart construction on a pair of nuclear reactors that were mothballed years ago. The state-owned utility is betting interest will be strong, with tech giants such as Amazon and Microsoft in need of clean energy to fuel AI.

Then, Google is making a fresh investment of more than $1 billion into AI startup Anthropic, the Financial Times reported on Wednesday. This comes after Reuters and other media reported earlier in January that Anthropic was nearing a $2 billion fundraise in a round, led by Lightspeed Venture Partners, valuing the firm at about $60 billion.

In videos, Indeed CEO Chris Hyams, and Stanford Digital Economy Lab Director Erik Brynjolfsson, join Bloomberg’s Work for a discussion on the key trends impacting employees and employers in 2025 and beyond.

Meanwhile, Sarah Friar, Chief Financial Officer of OpenAI warned that there is strong competition in the development of AI coming from China, recognizing the economic and security benefits of the emerging technology.

S Shirin Ghaffary at Bloomberg House in Davos. ‘ + s Erik Schatzker at Bloomberg House in Davos. + ll look at how Frames offers cinematic image outputs, best practices for prompting, and showcases user-generated examples. + Thats all for today, but AI is moving fast, subscribe today to stay informed. Please don’t forget to vote for me in the Entrepreneur of Impact Competition today! Thank you for supporting me and my partners, it’s how I keep NNN free.

Continue reading “US 0 Billion ‘Stargate’ AI Venture Fund Headed By Oracle, OpenAI, And SoftBank” | >

The Stargate Project is a new company which intends to invest $500 billion over the next four years building new AI infrastructure for OpenAI in the United States. We will begin deploying $100 billion immediately. This infrastructure will secure American leadership in AI, create hundreds of thousands of American jobs, and generate massive economic benefit for the entire world. This project will not only support the re-industrialization of the United States but also provide a strategic capability to protect the national security of America and its allies.

The initial equity funders in Stargate are SoftBank, OpenAI, Oracle, and MGX. SoftBank and OpenAI are the lead partners for Stargate, with SoftBank having financial responsibility and OpenAI having operational responsibility. Masayoshi Son will be the chairman.

Arm, Microsoft, NVIDIA, Oracle, and OpenAI are the key initial technology partners. The buildout is currently underway, starting in Texas, and we are evaluating potential sites across the country for more campuses as we finalize definitive agreements.

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Reservoir computing (RC) is a powerful machine learning module designed to handle tasks involving time-based or sequential data, such as tracking patterns over time or analyzing sequences. It is widely used in areas such as finance, robotics, speech recognition, weather forecasting, natural language processing, and predicting complex nonlinear dynamical systems. What sets RC apart is its efficiency―it delivers powerful results with much lower training costs compared to other methods.

RC uses a fixed, randomly connected network layer, known as the reservoir, to turn input data into a more complex representation. A readout layer then analyzes this representation to find patterns and connections in the data. Unlike traditional neural networks, which require extensive training across multiple network layers, RC only trains the readout layer, typically through a simple linear regression process. This drastically reduces the amount of computation needed, making RC fast and computationally efficient.

Inspired by how the brain works, RC uses a fixed network structure but learns the outputs in an adaptable way. It is especially good at predicting and can even be used on physical devices (called physical RC) for energy-efficient, high-performance computing. Nevertheless, can it be optimized further?

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