Latest news with #BG2
Time of India
16-07-2025
- Business
- Time of India
Meta hires two more OpenAI top researchers amid $300 million AI talent war: Report
Amid its AI hiring spree, Facebook-parent Meta has reportedly hired another two researchers – Jason Wei and Hyung Won Chung from Sam Altman-led OpenAI. According to a Wired report, OpenAI has deactivated the internal Slack account of both the researchers. As per the report, both Wei and Chung have a close working relationship. Meta has been on a hiring spree in recent times. The company has aggressively hired talent from rival companies – Apple, GoogleDeepMind, GitHub and others. Meta is allegedly offering up to $300 million over four years to its top AI talent. Who are OpenAI researchers Jason Wei and Hyung Won Chun that Meta has hired As per Wired report, Jason Wei worked on OpenAI's o3 and deep search models. He joined the company in 2023. Before OpenAI, he worked at Google on chain-of-thought research, that involves training an AI model to process complex queries step-by-step. A self-described 'diehard' at OpenAI, Wei became deeply passionate about reinforcement learning — a way of teaching AI by giving it rewards for good actions and penalties for mistakes. This method has become an important part of AI research, and many of the experts recently hired by Meta for its superintelligence team are specialists in this field. by Taboola by Taboola Sponsored Links Sponsored Links Promoted Links Promoted Links You May Like An engineer reveals: One simple trick to get internet without a subscription Techno Mag Learn More Undo Hyung Won Chung also joined OpenAI in 2023. He worked on some of the same projects at the company as Wei. These included deep research and OpenAI's o1 model. His research is primarily focused on reasoning and agents, the website says. Interestingly,. Chung overlapped with Wei at Google as well, and joined OpenAI at the same time as Wei. Dell CEO warns Mark Zuckerberg's AI hiring spree Dell CEO Michael Dell has raised concerns about the internal culture impact Meta may face due to its aggressive hiring of artificial intelligence talent from rivals – Google DeepMind, OpenAI, GitHub, Apple and others. Speaking on the BG2 podcast hosted by Bill Gurley and Brad Gerstner on Thursday, Dell warned that bringing in top AI professionals at high salaries could lead to dissatisfaction among existing staff at Meta Platforms. 'It'll be a challenge culturally for sure,' Dell said. He further explained that offering higher pay to new hires could make current employees feel left out or underappreciated, which may result in friction within teams and create a long line of 'complaining' employees outside CEO Mark Zuckerberg's office. EYVA Review: 60-Second Health Scan for Your Whole Family! AI Masterclass for Students. Upskill Young Ones Today!– Join Now
Time of India
11-07-2025
- Business
- Time of India
Dell CEO Michael Dell warns Meta's AI hiring spree may result in line of ‘complaining employees' outside CEO Mark Zuckerberg's office
Dell CEO Michael Dell has raised concerns about the internal culture impact Meta may face due to its aggressive hiring of artificial intelligence talent from rivals – Google DeepMind, OpenAI, GitHub, Apple and others. Speaking on the BG2 podcast hosted by Bill Gurley and Brad Gerstner on Thursday, Dell warned that bringing in top AI professionals at high salaries could lead to dissatisfaction among existing staff at Meta Platforms . 'It'll be a challenge culturally for sure,' Dell said. He further explained that offering higher pay to new hires could make current employees feel left out or underappreciated, which may result in friction within teams and create a long line of 'complaining' employees outside CEO Mark Zuckerberg's office. Emphasizing the importance of fairness in the workplace, he stated 'People generally have a sense of fairness, right? They want to be treated fairly relative to others and relative to the opportunities that they have out there in the overall market.' Dell further stated that while Meta's strategy and the 'math' may work if this is reduced to a 'race to super intelligence,' but he also warned against the potential for internal conflict and dissatisfaction should not be overlooked. Meta hiring push and industry reaction by Taboola by Taboola Sponsored Links Sponsored Links Promoted Links Promoted Links You May Like An engineer reveals: One simple trick to get internet without a subscription Techno Mag Learn More Undo Meta has significantly ramped up hiring through its Superintelligence Labs, launched in June to focus on artificial general intelligence (AGI). The company has hired talent from competitors such as OpenAI, Google DeepMind, Anthropic, and Apple. This talent war has reshaped the AI sector and drawn mixed reactions from industry leaders. Earlier, OpenAI CEO Sam Altman also criticized Meta's hiring strategy, calling it 'distasteful' and suggesting it may create issues inside the company. Altman even hinted that OpenAI might need to review its compensation policies in response to Meta's aggressive poaching. Reid Hoffman, cofounder of LinkedIn and former OpenAI board member, offered a different view. In an interview with CNBC, Hoffman said it makes economic sense for companies to spend big on AI talent if they want to stay ahead. Lava Storm Play First Look: Best Budget Phone Under Rs 10,000? AI Masterclass for Students. Upskill Young Ones Today!– Join Now
Forbes
10-04-2025
- Business
- Forbes
Not Everything Is An Agent
Ian Gotts, founder and CEO at getty It is easy to be caught up in the excitement of this new, exciting, agentic world. Everything you look at could be an agent, replacing boring form-based workflows. Recently, Microsoft CEO Satya Nadella, talking to Bill Gurley and Brad Gerstner on their BG2 podcast, suggested that business applications could 'collapse' in the agentic AI era. His view was SaaS would be CRUD database with agents on top. But not everything is an agent. Some of the earliest agents we built didn't necessarily need to be, but we wanted to deploy them just to get the experience of building an agent. For example, an employee booking their PTO. What was interesting was thinking about the process showed us the existing workflow we'd built had flaws. And while it would work as a workflow, it is much nicer as an agent. We also discovered that building the agent was far easier than coding it and that it could be built, tested and deployed by a junior business analyst. This got us thinking about the criteria to determine whether to build an agent or simply create a workflow linked to a button: • Do you want to shield/isolate the user from your terminology/notation/process? In our PTO example, an employee can say, "I want to take time off / I need to book PTO / I need to schedule vacation / I was off last week," and the agent understands. • Is the input unstructured data? Agents are great at making sense of this. An example would be pulling information from a call transcript and suggesting updates to the related opportunity. Another example is our agent that provides coaching roleplay to our sales teams based on a customer call transcript. • Do you need to perform complex reasoning that would be complex to code? In our PTO example, we don't want employees to book time on a weekend or public holiday. We used a simple prompt template that has access to weekends and public holidays in the UK and U.S., and the agent understands them. • Do you have complex validation rules where a rule is based on multiple field values? Again, an agent handles these if you give it the target output and think through the process. The PTO example requires you to provide a start date and length of PTO that is not on a weekend/public holiday and does not span a calendar year, and you need enough left in your balance for the year based on the policies for your country and seniority. And you cannot book PTO in less than 1/2 increments. This is complex logic, but it's just a few agent instructions. Easy to write, review, test and debug. • Do you need some form of planning that cannot be coded? For example, constructing a quote based on criteria: A customer wants X licenses and has a maximum budget of $Y but is prepared to do a one-, two- or three-year deal, so what is the best way to structure it? • Is it critical that the data is correct? Form filling can be overridden by users selecting the first dropdown or putting "..." in a mandatory field. The agent can guide them to the correct answer but also reduce the effort because it can use context to pre-fill information. As we get more patterns for agents, and the pricing is more transparent and realistic, then many automations could cost-effectively be replaced with agents. But at the moment, ROI and cost shouldn't be the gating factor. This is a major disruption, and you need to start building agents to ensure you have the right foundations in place: well-understood business processes, strong data governance and data quality, documented systems metadata. And all this must be underpinned by a rapid but governed implementation lifecycle because agents will iterate fast at the beginning. Every organization will find use cases for agents that will provide a huge competitive advantage. But this is only going to happen if you start experimenting. It's only when you get started that you will be able to uncover even more valuable use cases. Let's look at process configuration mining, for example. We've built an agent that can take a system's metadata and document how it works as a process diagram. Not how you think it works. Not how you remembered it working. Not how the consultants said it worked. Not how the design document said it should work. How it actually works. The process configuration mining agent is a combination of code and agent actions. It wouldn't have been possible without the AI capabilities, which are an enabler. So not everything is an agent. But unless you start using simpler use cases, you may never discover a step change example. Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?
