Skip to main content

AI Agents and the Latest Silicon Valley Hype


In what appears to be yet another grandiose proclamation from the tech industry, Google has released a whitepaper extolling the virtues of what they're calling "Generative AI agents". (https://www.aibase.com/news/14498) Whilst the basic premise—distinguishing between AI models and agents—holds water, one must approach these sweeping claims with considerable caution.

Let's begin with the fundamentals. Yes, AI models like Large Language Models do indeed process information and generate outputs. That much isn't controversial. However, the leap from these essentially sophisticated pattern-matching systems to autonomous "agents" requires rather more scrutiny than the tech evangelists would have us believe.

The whitepaper's architectural approaches—with their rather grandiose names like "ReAct" and "Tree of Thought"—sound remarkably like repackaged versions of long-standing computer science concepts, dressed up in fashionable AI clothing. One cannot help but wonder whether Silicon Valley's penchant for reinventing the wheel is at play here.

Perhaps most eyebrow-raising are the projected impacts on the workforce. The claim that AI agents could save 25% of private-sector workforce time in the UK—equivalent to 6 million workers—seems suspiciously precise for such a nascent technology. One recalls similar bold predictions about previous technological revolutions that failed to materialise quite as dramatically as forecast. https://institute.global/insights/economic-prosperity/the-impact-of-ai-on-the-labour-market)

Even more telling is the Salesforce study revealing that 76% of UK workers feel pressured to upskill in AI, whilst more than half are too embarrassed to admit using it to their managers. This rather neatly encapsulates the contradiction at the heart of the AI revolution: simultaneously overhyped and poorly understood.

As for OpenAI's Sam Altman predicting AI agents joining the workforce by 2025, one might gently remind readers of the tech industry's rather patchy track record with timelines. Remember when self-driving cars were just around the corner? Or when blockchain was going to revolutionise everything from banking to banana farming?

Whilst there's undoubtedly potential in these technologies, perhaps we'd do well to maintain a healthy dose of scepticism about claims of imminent workplace transformation. After all, the gap between PowerPoint promises and practical implementation has historically been rather wider than the Silicon Valley prophets would have us believe.

Labels:

Comments

Post a Comment

Popular posts from this blog

The AI Dilemma and "Gollem-Class" AIs

From the Center for Humane Technology Tristan Harris and Aza Raskin discuss how existing A.I. capabilities already pose catastrophic risks to a functional society, how A.I. companies are caught in a race to deploy as quickly as possible without adequate safety measures, and what it would mean to upgrade our institutions to a post-A.I. world. This presentation is from a private gathering in San Francisco on March 9th with leading technologists and decision-makers with the ability to influence the future of large-language model A.I.s. This presentation was given before the launch of GPT-4. One of the more astute critics of the tech industry, Tristan Harris, who has recently given stark evidence to Congress. It is worth watching both of these videos, as the Congress address gives a context of PR industry and it's regular abuses. "If we understand the mechanisms and motives of the group mind, it is now possible to control and regiment the masses according to our will without their...
Post a Comment
Read more

CRM and AI?

Artificial intelligence (AI) can be used in a CRM system to enhance customer service, sales performance, and marketing strategies. Here are some examples of how AI can be applied in a CRM: - AI can enable natural language processing and voice input, such as Siri or Alexa, to allow a CRM system to answer customer queries, solve their problems, and even identify new opportunities for the sales team. Some AI-driven CRM systems can even multitask to handle all these functions and more. - AI can help with sales forecasting by analysing historical data, customer behaviour, and market trends. This can help the sales team make more accurate predictions for future sales figures and determine a success metric. - AI can assist with lead management by automating the process of qualifying and nurturing prospects. It can use chatbots and email bots to understand leads' needs and inform the sales team to improve their performance. With insights gained from these bots, companies can optimise their...
Post a Comment
Read more

A Network Analysis Tool to help identify structural gaps

  InfraNodus is a web-based open source tool and method for generating insight from any text or discourse using text network analysis. The byline on the website states, 'Get an overview of any discourse, reveal the blind spots, enhance your perspective.' which, whilst accurate does little to summarise the potential of such a tool. Watching the introduction helps. Its capabilities include representing any text as a network and identifying the most influential words in a discourse based on the terms' co-occurrence, providing text network visualization and analysis live as new data is added, offering discourse structure analysis to measure the level of bias in discourse and identify structural gaps in discourse, and being available via an API to be used in conjunction with other text mining and analysis software. The white paper, ' Generating Insight Using Text Network Analysis ' concludes:  'The tool is currently used by researchers, marketing professionals, stude...
Post a Comment
Read more