
DeepLearnHS Podcast Explores AI's Role in Transforming the Workplace
DeepLearnHS is launching a new podcast designed to explore how AI is transforming the world of work.
The series kicks off with an inaugural episode, Impact of AI: Hiring, Workforce Management, and Employee Experience, which considers how businesses are using AI to attract, retain and optimise talent.
The podcast is produced in collaboration with Business News Wales as part of the media firm's podcast production service. Carwyn Jones is the podcast host.
Future episodes will look at AI in skills and training, and AI in education and policy.
Chris Butt, CEO & Founder, DeepLearnHS, said:
'The world of work is rapidly changing, with AI influencing every step of an individual's journey from the classroom through to recruitment, training and retention across their entire career.
'Some organisations are at the forefront of adopting these innovations, whilst others are more cautious in their implementation. With this podcast we want to facilitate discussion, showcase best practice and empower listeners to embrace technology in the knowledge that it can enhance human potential and not replace it.'
The first episode is now available on all major platforms, including Apple Podcasts and Spotify.
Listen to the DeeplearnHS podcast series here

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Daily Mail
5 hours ago
- Daily Mail
The silent bloodbath that's tearing through the middle-class and rapidly flipping the US economy on its head
Elon Musk and hundreds of other tech mavens wrote an open letter two years ago about how AI was coming to 'automate away all the jobs' and upend society. It looks like we should have listened to them. Layoffs are sweeping America, nixing hundreds of thousands of jobs at Microsoft, Walmart, and other titans. The newly jobless speak of a 'bloodbath' on the scale of the pandemic. This time, it's not blue-collar and factory workers getting whacked — it's college graduates with white-collar jobs in tech, finance, law, and consulting. Entry-level jobs are vanishing the fastest — stoking fears of recession and a generation of disillusioned graduates left stranded with CVs no one wants. College grads are now much more likely to be unemployed than others, official data show. Chatbots have already taken over data entry and customer service jobs. Next-generation 'agentic' AI can solve problems, adapt, and work independently. These 'smartbots' are already spotting market trends, running logistics operations, writing legal contracts, and diagnosing patients. The markets have seen the future: AI investment funds are growing by as much as 60 percent a year. 'The AI layoffs have begun, and they're not stopping,' says tech entrepreneur Alex Finn. Luddites who don't embrace the tech 'will be completely irrelevant in the next five years,' he posted on X. Procter & Gamble, which makes diapers, laundry detergent, and other household items, this week said it would cut 7,000 jobs, or about 15 percent of non-manufacturing roles. Its two-year restructuring plan involves shedding managers who can be automated away. Microsoft last month announced a cull of 6,000 staff — about 3 percent of its workforce — targeting managerial flab, after a smaller round of performance-related cuts in January. LA-based tech entrepreneur Jason Shafton said the software giant's layoffs spotlight a trend 'redefining' the job market. 'If AI saves each person 10 percent of their time (and let's be real, it's probably more), what does that mean for a company of 200,000?' he wrote. Retail titan Walmart, America's biggest private employer, is slashing 1,500 tech, sales, and advertising jobs in a streamlining effort. Citigroup, cybersecurity firm CrowdStrike, Disney, online education firm Chegg, Amazon, and Warner Bros. Discovery have culled dozens or even hundreds of their workers in recent weeks. Musk himself led a federal sacking spree during his 130-day stint at the Department of Government Efficiency, which ended on May 30. Federal agencies lost some 135,000 to firings and voluntary resignation under his watch, and 150,000 more roles are set to be mothballed. Memes like this being shared on social media reveal how badly white-collar jobs have been hit Employers had already announced 220,000 job cuts by the end of February, the highest layoff rate seen since 2009. In announcing cuts, executives often talk about restructuring and tough economic headwinds. Many are spooked by US President Donald Trump's on-and-off tariffs, which sent stock markets into free-fall and prompted CEOs to second-guess their long-term plans. Others say something deeper is happening, as companies embrace the next-generation models of chatbots and AI. Robots and machines have for decades usurped factory workers. AI chatbots have more recently replaced routine, repetitive, data entry and customer service roles. A new and more sophisticated technology — called Agentic AI — now operates more independently: perceiving the environment, setting goals, making plans, and executing them. AI-powered software now writes reports, analyses spreadsheets, creates legal contracts, designs logos, and even drafts press releases, all in seconds. Banks are axing graduate recruitment schemes. Law firms are replacing paralegals with AI-driven tools. Even tech startups, the birthplace of innovation, are swapping junior developers for code-writing bots. Managers increasingly seek to become 'AI first' and test whether tasks can be done by AI before hiring a human. That's now company policy at Shopify. It's how fintech firm Klarna shrank its headcount by 40 percent, CEO Sebastian Siemiatkowski told CNBC last month. Experienced workers are encouraged to automate tasks and get more work done; recent graduates are struggling to get their foot in the door. From a distance, the job market looks relatively buoyant, with unemployment holding steady at 4.2 percent for the third consecutive month, the Labor Department reported on Friday. But it's unusually high — close to 6 percent — among recent graduates. The Federal Reserve Bank of New York recently said job prospects for these workers had 'deteriorated noticeably.' That spells trouble not just for young workers, but for the long-term health of businesses — and the economy. Economists warn of an AI-induced downturn, as millions lose jobs, spending plummets, and social unrest festers. It's been dubbed an industrial revolution for the modern era, but one that's measured in years, not decades. Dario Amodei, CEO of Anthropic, one of the world's most powerful AI firms, says we're at the start of a storm. AI could wipe out half of all entry-level white-collar jobs — and spike unemployment to 10-20 percent in the next one to five years, he told Axios. Lawmakers have their heads in the sand and must stop 'sugar-coating' the grim reality of the late 2020s, Amodei said. 'Most of them are unaware that this is about to happen,' he said. Sacked workers have taken to social media to vent their frustrations about the new tech crunch 'It sounds crazy, and people just don't believe it.' Young people who've been culled are taking to social media to vent their anger as the door to a middle-class lifestyle closes on them. Patrick Lyons calls it 'jarring and unexpected' how he lost his Austin-based program managing job in an 'emotionless business decision' by Microsoft. 'There's nothing the 6,000 of us could have done to prevent this,' he posted. A young woman coder, known by her TikTok handle dotisinfluencing, posts a daily video diary about the 'f*****g massacre' of layoffs at her tech company as 'AI is taking over,' she says. Her job search is going badly — one recruiter appeared more interested in taking her out for drinks than offering a paycheck, she said. 'I feel like s**t,' she added. Ben Wolfson, a young Meta software engineer, says entry-level software jobs dried up in 2023. 'Big tech doesn't want you, bro,' he says. Critics say universities are churning out graduates into a market that simply doesn't need them. A growing number of young professionals say they feel betrayed — promised opportunity, but handed a future of 'AI-enhanced' redundancy. Others are eyeing an opportunity for a payout to try something different. Donald King posted a recording of the meeting in which he was unceremoniously laid off from his data science job at consulting firm PwC. 'RIP my AI factory job,' he said. 'I built the thing that destroyed me.' He now posts from Porto, in Portugal — a popular spot for digital nomads — where he's founded a marketing startup. Industry insiders say it won't be long before another generation of AI arrives to automate new sectors. As AI improves, the difference between 'safe' and 'automatable' work gets blurrier by the day. Human workers are advised to stay one step ahead and build AI into their own jobs to increase productivity. Optimists point to such careers as radiology — where humans initially looked set to be outmoded by machines that could speedily read medical scans and pinpoint tumors. But the layoffs didn't happen. The technology has been adopted — but radiologists adapted, using AI to sharpen images and automate some tasks, and boost productivity. Some radiology units even expanded their increasingly efficient human workforce. Others say AI is a scapegoat for 2025's job cuts — that executives are downsizing for economic reasons, and blaming technology so as not to panic shareholders. But for those who have lost their jobs, the future looks bleak.


Geeky Gadgets
12 hours ago
- Geeky Gadgets
Stop AI Hallucinations : Transform Your n8n Agent into a Precision Powerhouse
What if your AI agent could stop making things up? Imagine asking it for critical data or a precise task, only to receive a response riddled with inaccuracies or irrelevant details. These so-called 'hallucinations' are more than just a nuisance—they can derail workflows, undermine trust, and even lead to costly mistakes. But here's the good news: by fine-tuning your n8n AI agent settings, you can dramatically reduce these errors and unlock a level of performance that's both reliable and context-aware. From selecting the right chat model to configuring memory for seamless context retention, the right adjustments can transform your AI from unpredictable to indispensable. In this comprehensive guide, FuturMinds take you through the best practices and critical settings to optimize your n8n AI agents for accuracy and efficiency. Learn how to choose the perfect chat model for your needs, fine-tune parameters like sampling temperature and frequency penalties, and use tools like output parsers to ensure structured, reliable responses. Whether you're aiming for professional-grade results in technical workflows or simply want to minimize hallucinations in everyday tasks, this report will equip you with actionable insights to achieve your goals. Because when your AI agent performs at its best, so do you. n8n AI Agent Configuration Choosing the Right Chat Model The foundation of a reliable AI agent begins with selecting the most suitable chat model. Each model offers unique capabilities, and aligning your choice with your specific use case is crucial for optimal performance. Consider the following options: Advanced Reasoning: Models like Anthropic or OpenAI GPT-4 are designed for complex problem-solving and excel in tasks requiring nuanced understanding. Models like Anthropic or OpenAI GPT-4 are designed for complex problem-solving and excel in tasks requiring nuanced understanding. Cost Efficiency: Lightweight models such as Mistral are ideal for applications where budget constraints are a priority without compromising too much on functionality. Lightweight models such as Mistral are ideal for applications where budget constraints are a priority without compromising too much on functionality. Privacy Needs: Self-hosted options like Olama provide enhanced data control, making them suitable for sensitive or proprietary information. Self-hosted options like Olama provide enhanced data control, making them suitable for sensitive or proprietary information. Multimodal Tasks: For tasks involving both text and images, models like Google Gemini or OpenAI's multimodal models are highly effective. To improve efficiency, consider implementing dynamic model selection. This approach routes tasks to the most appropriate model based on the complexity and requirements of the task, making sure both cost-effectiveness and performance. Fine-Tuning AI Agent Parameters Fine-tuning parameters is a critical step in shaping your AI agent's behavior and output. Adjusting these settings can significantly enhance the agent's performance and reliability: Frequency Penalty: Increase this value to discourage repetitive responses, making sure more diverse and meaningful outputs. Increase this value to discourage repetitive responses, making sure more diverse and meaningful outputs. Sampling Temperature: Use lower values (e.g., 0.2) for factual and precise outputs, while higher values (e.g., 0.8) encourage creative and exploratory responses. Use lower values (e.g., 0.2) for factual and precise outputs, while higher values (e.g., 0.8) encourage creative and exploratory responses. Top P: Control the diversity of responses by limiting the probability distribution, which helps in generating more focused outputs. Control the diversity of responses by limiting the probability distribution, which helps in generating more focused outputs. Maximum Tokens: Set appropriate limits to balance response length and token usage, avoiding unnecessarily long or truncated outputs. For structured outputs such as JSON, combining a low sampling temperature with a well-defined system prompt ensures accuracy and consistency. This approach is particularly useful for technical applications requiring predictable and machine-readable results. Best n8n AI Agent Settings Explained Watch this video on YouTube. Stay informed about the latest in n8n AI agent configuration by exploring our other resources and articles. Configuring Memory for Context Retention Memory configuration plays a vital role in maintaining context during multi-turn conversations. Proper memory management ensures that responses remain coherent and relevant throughout the interaction. Key recommendations include: Context Window Length: Adjust this setting to retain essential information while staying within token limits, making sure the agent can reference prior exchanges effectively. Adjust this setting to retain essential information while staying within token limits, making sure the agent can reference prior exchanges effectively. Robust Memory Nodes: For production environments, use reliable options like PostgreSQL chat memory via Supabase to handle extended interactions without risking data loss or crashes. Avoid using simple memory nodes in production, as they may not provide the stability and scalability required for complex or long-running conversations. Enhancing Functionality with Tool Integration Integrating tools expands your AI agent's capabilities by allowing it to perform specific actions via APIs. This functionality is particularly useful for automating tasks and improving efficiency. Examples include: Email Management: Integrate Gmail to send, organize, and manage emails directly through the AI agent. Integrate Gmail to send, organize, and manage emails directly through the AI agent. Custom APIs: Add domain-specific tools for specialized tasks, such as retrieving financial data, generating reports, or managing inventory. To minimize hallucinations, clearly define the parameters and scope of each tool. This ensures the agent understands its limitations and uses the tools appropriately within the defined context. Optimizing System Prompts A well-crafted system prompt is essential for defining the AI agent's role, goals, and behavior. Effective prompts should include the following elements: Domain Knowledge: Specify the agent's expertise and focus areas to ensure it provides relevant and accurate responses. Specify the agent's expertise and focus areas to ensure it provides relevant and accurate responses. Formatting Rules: Provide clear instructions for structured outputs, such as JSON, tables, or bullet points, to maintain consistency. Provide clear instructions for structured outputs, such as JSON, tables, or bullet points, to maintain consistency. Safety Instructions: Include guidelines to prevent inappropriate, harmful, or biased responses, making sure ethical and responsible AI usage. Using templates for system prompts can streamline the configuration process and reduce errors, especially when deploying multiple agents across different use cases. Using Output Parsers Output parsers are invaluable for enforcing structured and predictable responses. They are particularly useful in applications requiring machine-readable outputs, such as data pipelines and automated workflows. Common types include: Structured Output Parser: Ensures responses adhere to predefined formats, such as JSON or XML, for seamless integration with other systems. Ensures responses adhere to predefined formats, such as JSON or XML, for seamless integration with other systems. Item List Output Parser: Generates clear and organized lists with specified separators, improving readability and usability. Generates clear and organized lists with specified separators, improving readability and usability. Autofixing Output Parser: Automatically corrects improperly formatted outputs, reducing the need for manual intervention. Incorporating these tools enhances the reliability and usability of your AI agent, particularly in technical and data-driven environments. Additional Settings for Enhanced Performance Fine-tuning additional settings can further improve your AI agent's reliability and adaptability. Consider the following adjustments: Iteration Limits: Set a maximum number of iterations for tool usage loops to prevent infinite cycles and optimize resource usage. Set a maximum number of iterations for tool usage loops to prevent infinite cycles and optimize resource usage. Intermediate Steps: Enable this feature to debug and audit the agent's decision-making process, providing greater transparency and control. Enable this feature to debug and audit the agent's decision-making process, providing greater transparency and control. Multimodal Configuration: Ensure the agent can handle binary image inputs for tasks involving visual data, expanding its range of applications. These settings provide greater control over the agent's behavior, making it more versatile and effective in handling diverse scenarios. Best Practices for Continuous Improvement Building and maintaining a high-performing AI agent requires ongoing monitoring, testing, and refinement. Follow these best practices to ensure optimal performance: Regularly review and adjust settings to enhance response quality, reduce token usage, and address emerging requirements. Test the agent in real-world scenarios to identify potential issues and implement necessary improvements. Align tools, configurations, and prompts with your specific use case and objectives to maximize the agent's utility and effectiveness. Consistent evaluation and optimization are essential for making sure your AI agent remains reliable, efficient, and aligned with your goals. Media Credit: FuturMinds Filed Under: AI, Guides Latest Geeky Gadgets Deals Disclosure: Some of our articles include affiliate links. If you buy something through one of these links, Geeky Gadgets may earn an affiliate commission. Learn about our Disclosure Policy.


Telegraph
14 hours ago
- Telegraph
‘I'm the world's youngest self-made female billionaire'
A 30-year-old US tech entrepreneur born to immigrant parents has unseated Taylor Swift as the world's youngest self-made female billionaire. Lucy Guo, who is worth an estimated $1.3bn (£1bn) according to Forbes, told The Telegraph that her new title 'doesn't really feel like much'. 'I think that maybe reality hasn't hit yet, right? Because most of my money is still on paper,' she said. Ms Guo's wealth stems from her 5pc stake in Scale AI, a company she co-founded in 2016. The artificial intelligence (AI) business is currently raising money in a deal likely to value it at $25bn. That valuation – and the billionaire status it has bestowed upon Ms Guo – underlines the current AI boom, which has reinvigorated Silicon Valley and is now reshaping the world. Everyone from Mark Zuckerberg to Sir Keir Starmer have praised the potential of the technology, which is forecast to save billions but may also destroy scores of jobs. The AI craze has caused the founders and chief executives of companies in the space to climb the world's rich list as they cash in on soaring valuations and increasing demand for their companies' technologies. Ms Guo is also an exemplar of the American dream. Born to Chinese immigrant parents, she dropped out of Carnegie Mellon University to find her fortune. Like Mr Zuckerberg before her, the decision to ditch traditional education in favour of entrepreneurship has now paid off handsomely. Still, it was not a decision her parents approved of at the time. 'They stopped talking to me for a while – which is fine,' she said. 'I get it, because, you know, the immigrant mentality was like, 'we sacrificed everything, we came to a new country, left all our relatives behind, to try to give our kids a better future'. 'I think they viewed it as a sign of disrespect. They're like, 'wow, you don't appreciate all the sacrifices we did for you, and you don't love us'. So they were extremely hurt.' They have since reconciled. In her first year of college, Ms Guo took part in hackathons and coding competitions, helping her to realise that 'you can just create a startup out of like, nothing'. She was awarded a Thiel Fellowship, which provides recipients with $200,000 over two years to support them to drop out of university and pursue other work, such as launching a startup. The fellowship is funded by Peter Thiel, the former PayPal chief executive. Mr Thiel, who donated $1.25m to Donald Trump's 2016 presidential campaign, has been an enthusiastic supporter of entrepreneurship, and also co-founded Palantir, the data analytics and AI software firm now worth billions. Ms Guo initially tried to found a company based around people selling their home cooking to others. While the business did well financially, it faced food safety problems and ultimately failed. After stints at Quora, the question-and-answer website, and Snapchat, Ms Guo launched Scale AI with co-founder Alexandr Wang in 2016. The company labels the data used to develop applications for AI. The timing was perfect: OpenAI had been founded a year earlier and uses Scale AI's technology to help train ChatGPT, the generative AI chatbot. OpenAI is one of the leading lights of the new AI boom and has a valuation of $300bn. Like Ms Guo, its founder and boss Sam Altman is now a billionaire. Ms Guo left Scale AI only two years after helping to found it – 'ultimately there was a lot of friction between me and my co-founder' – but retained her stake, a decision that helped propel her into the ranks of the world's top 1pc. 'It's not like I'm flying PJs [private jets] everywhere. Just occasionally, just when other people pay for them. I'm kidding – sometimes I pay for them,' Ms Guo said, laughing. After leaving Scale AI, Ms Guo went on to set up her own venture capital fund, Backend Capital, which has so far invested in more than 100 startups. She has also run HF0, an AI business accelerator. Ms Guo is particularly passionate about supporting female entrepreneurs: 'If you take two people that are exactly the same, male and female, they come out of MIT as engineers, I think that subconsciously every investor thinks the male is going to do better, which sucks.' However, she is demanding of companies she backs. 'If you care about work-life balance, go work at Google, you'll get paid a high salary and you'll have that work-life balance,' she said. 'If you're someone that wants to build a startup, I think it's pretty unrealistic to build a venture-funded startup with work-life balance.' 'Number one party girl' Ms Guo's work-life balance has itself been the subject of tabloid attention. After leaving Scale AI she was dubbed 'Miami's number one party girl' by the New York Post for raucous celebrations held at her multimillion-dollar flat in the city's One Thousand Museum tower, which counts David Beckham among its residents. One 2022 party involved a lemur and snake rented from the Zoological Wildlife Foundation, and led to the building's homeowners' association sending a warning letter. While she still owns her residence in Miami, Ms Guo lives in Los Angeles. Alongside investing, Ms Guo has started a new business, Passes, which lets users sell access to themselves online through paid direct messages, livestreaming and subscriptions. Creators on the platform include TikTok influencer Emma Norton, actor Bella Thorne and the music producer Kygo. It is pitched as a competitor to Patreon, a platform that lets musicians and artists sell products and services directly to fans. However, the business also occupies the same space as OnlyFans, the platform known for hosting adult videos and images, and Passes has faced claims that it knowingly distributed sexually explicit material featuring minors. A legal complaint filed by OnlyFans model Alice Rosenblum claimed the platform produced, possessed and sold sexually explicit content featuring her when she was underage. The claims are strongly denied by the company. A spokesman for Passes said: 'This lawsuit is part of an orchestrated attempt to defame Passes and Ms Guo, and these claims have no basis in reality. As explained in the motion to dismiss filed on April 28, Ms Guo and Passes categorically reject the baseless allegations made against them in the lawsuit.' Scrutiny of Passes and Ms Guo herself is only likely to intensify following her crowning by Forbes. However, she is sceptical that she will hold on to the title of youngest self-made female billionaire for long. 'I have almost no doubt this title can be taken in three to six months,' she said, adding: 'Every single time it was taken, it's like, OK, there's more innovation happening – women are crushing it. 'I think I'm personally excited for someone else to take that title, because that's a sign entrepreneurship is growing.'