New York state has required companies to disclose if "technological innovation or automation" was the cause of job loss for nearly a year. Over 160 companies in New York state have filed notices of mass layoffs since last March. None--in a group that includes Amazon, Goldman Sachs, and other employers that are adopting AI tools --attributed their workforce cuts in those filings to "technological innovation or automation." That option was added 11 months ago to a required question on paperwork that businesses with 50 or more employees must file with the state to notify of sizable job losses. New York's Department of Labor told WIRED that, as of the end of January, no employer had marked tech as the reason for their workforce reduction.

Tech companies like to make two grand pronouncements about the future of artificial intelligence. First, the technology is going to usher in a revolution akin to the advent of fire, nuclear weapons, and the internet. And second, it is going to cost almost unfathomable sums of money. Silicon Valley has already triggered tens or even hundreds of billions of dollars of spending on AI, and companies only want to spend more. Their reasoning is straightforward: These companies have decided that the best way to make generative AI better is to build bigger AI models.

This report outlines a transformative initiative in the financial investment industry, where the conventional decision-making process, laden with labor-intensive tasks such as sifting through voluminous documents, is being reimagined. Leveraging language models, our experiments aim to automate information summarization and investment idea generation. We seek to evaluate the effectiveness of fine-tuning methods on a base model (Llama2) to achieve specific application-level goals, including providing insights into the impact of events on companies and sectors, understanding market condition relationships, generating investor-aligned investment ideas, and formatting results with stock recommendations and detailed explanations. Through state-of-the-art generative modeling techniques, the ultimate objective is to develop an AI agent prototype, liberating human investors from repetitive tasks and allowing a focus on high-level strategic thinking. The project encompasses a diverse corpus dataset, including research reports, investment memos, market news, and extensive time-series market data. We conducted three experiments applying unsupervised and supervised LoRA fine-tuning on the llama2_7b_hf_chat as the base model, as well as instruction fine-tuning on the GPT3.5 model. Statistical and human evaluations both show that the fine-tuned versions perform better in solving text modeling, summarization, reasoning, and finance domain questions, demonstrating a pivotal step towards enhancing decision-making processes in the financial domain. Code implementation for the project can be found on GitHub: https://github.com/Firenze11/finance_lm.

Kara Frederick, tech director at the Heritage Foundation, discusses the need for regulations on artificial intelligence as lawmakers and tech titans discuss the potential risks. Since the November 2022 launch of OpenAI's ChatGPT (Generative Pre-trained Transformers), the issue of AI technologies-related job displacement is receiving renewed economic impact scrutiny. For example, in March 2023, technology firm OpenAI released a report that found at least 80% of the U.S. labor force could have at least 10% of their work-related tasks affected by the introduction of GPT, while another 19% of employees may see at least 50% of these work-related tasks impacted. While GPT influence impacts all wage levels, the higher-income jobs potentially face the greatest exposure, concludes OpenAI. Also in March 2023, researchers at investment banker Goldman Sachs, after collecting data on occupationally-oriented tasks in Europe and the U.S., found that roughly two-thirds of current occupations are exposed to varying degrees of generative AI automation (such as found in ChatGPT), and that AI could substitute for nearly one-fourth of current work performed.

Argenti also likened the advent of powerful generative artificial intelligence systems such as ChatGPT to the invention of the printing press, and predicted the technology will transform how businesses store and organize institutional knowledge, according to the email. He also raised the question of whether A.I. could make rising inequality worse. Goldman Sachs declined to comment on Argenti's message. In the email, Argenti said that while others have said generative A.I. will be more impactful than the discovery of fire, the debut of the internet, or the move to cloud computing, he believed that a better analogy is the invention of the printing press, which had the effect of both democratizing access to knowledge as well as massively accelerating the codification of knowledge. Argenti said that while "efficiency gains are capturing a lot of the mindshare" he believed "LLMs are a breakthrough in knowledge more than they are in productivity."

At the speed, at which the advancement of artificial intelligence (AI) is being witnessed, it has the potential to significantly disrupt labour markets globally. And this is certified in the research done by Goldman Sachs.

As many as 300 million full-time jobs around the world could be automated in some way by the newest wave of artificial intelligence that has spawned platforms like ChatGPT, according to Goldman Sachs economists. They predicted in a report Sunday that 18% of work globally could be computerized, with the effects felt more deeply in advanced economies than emerging markets. That's partly because white-collar workers are seen to be more at risk than manual laborers. Administrative workers and lawyers are expected to be most affected, the economists said, compared to the "little effect" seen on physically demanding or outdoor occupations, such as construction and repair work. In the United States and Europe, approximately two-thirds of current jobs "are exposed to some degree of AI automation," and up to a quarter of all work could be done by AI completely, the bank estimates.

Goldman Sachs is experimenting with generative AI tools internally to help its developers automatically generate and test code, the company's chief information officer told CNBC. Marco Argenti, who joined Goldman as a partner from Amazon in 2019, said Tuesday that the firm's software engineers have been using the technology to automatically generate lines of code. It is currently in a "proof of concept" stage and not yet ready for production, he added. "Developers are already using some of the assisted coding technology," Argenti told CNBC's Arjun Kharpal at the Goldman Sachs technology symposium on Tuesday. Generative AI refers to a group of products that produce human-like text or images in response to written prompts from users.

Ramp is building the next generation of finance tools--from corporate cards and expense management, to bill payments and accounting integrations--designed to save businesses time and money with every click. Over 12,000 customers cut their expenses by 3.5% per year and close their books 8x faster by switching to the Ramp platform. Founded in 2019, Ramp powers the fastest-growing corporate card and bill payment software in America and enables billions of dollars of purchases each year. Ramp continues to grow quickly, more than doubling its revenue run rate in the first half of 2022. Valued at $8.1 billion, Ramp's investors include Founders Fund, Stripe, Citi, Goldman Sachs, Coatue Management, D1 Capital Partners, Redpoint Ventures, General Catalyst, and Thrive Capital, as well as over 100 angel investors who were founders or executives of leading companies.

The last few years have been a major accelerator for the robotics industry at large, but warehouse robotics may be the biggest winner of all. Stay at home orders fueled adoption in the early days of the pandemic, as some retailers stayed open after being labeled "essential businesses." Even after things began reopening, those roles have remained difficult to fill, leading many firms to look toward robotic help. All the while, Amazon has had a jump on most of the industry, dating back to the company's acquisition of Kiva Systems a decade ago. The competition continues looking for angles to compete with the 800-pound e-commerce gorilla, and robotics startups have flooded the field, promising an edge.