{"id":93505,"date":"2024-11-19T08:23:38","date_gmt":"2024-11-19T13:23:38","guid":{"rendered":"https:\/\/danielschristian.com\/learning-ecosystems\/?p=93505"},"modified":"2024-11-19T13:21:34","modified_gmt":"2024-11-19T18:21:34","slug":"miscommunication-leads-ai-based-hiring-tools-astray-adigaskell-org-other-items-re-ai-in-general","status":"publish","type":"post","link":"http:\/\/danielschristian.com\/learning-ecosystems\/2024\/11\/19\/miscommunication-leads-ai-based-hiring-tools-astray-adigaskell-org-other-items-re-ai-in-general\/","title":{"rendered":"“Miscommunication Leads AI-Based Hiring Tools Astray” [adigaskell.org] + other items re: AI in general"},"content":{"rendered":"

Miscommunication Leads AI-Based Hiring Tools Astray<\/strong><\/a>\u00a0— from adigaskell.org<\/p>\n

Nearly every Fortune 500 company now uses artificial intelligence (AI) to screen resumes and assess test scores to find the best talent. However, new\u00a0research<\/a>\u00a0from the University of Florida suggests these AI tools might not be delivering the results hiring managers expect.<\/p>\n

The problem stems from a simple miscommunication between humans and machines: AI thinks it\u2019s picking someone to hire, but hiring managers only want a list of candidates to interview.<\/strong><\/span><\/p>\n

Without knowing about this next step, the AI might choose safe candidates. But if it knows there will be another round of screening, it might suggest different and potentially stronger candidates.<\/span><\/strong><\/p><\/blockquote>\n

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AI agents explained: Why OpenAI, Google and Microsoft are building smarter AI agents<\/strong><\/a> — from digit.in by Jayesh Shinde<\/p>\n

In the last two years, the world has seen a lot of breakneck advancement in the Generative AI space, right from text-to-text, text-to-image and text-to-video based Generative AI capabilities. And all of that\u2019s been nothing short of stepping stones for the next big AI breakthrough \u2013 AI agents. According to\u00a0Bloomberg, OpenAI is preparing to launch its first autonomous AI agent, which is codenamed \u2018Operator,\u2019 as soon as in January 2025.<\/p>\n

Apparently, this OpenAI agent \u2013 or Operator, as it\u2019s codenamed \u2013 is designed to perform complex tasks independently. By understanding user commands through voice or text, this AI agent will seemingly do tasks related to controlling different applications in the computer, send an email, book flights, and no doubt other cool things. Stuff that ChatGPT, Copilot, Google Gemini or any other LLM-based chatbot just can\u2019t do on its own.<\/p>\n

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2025: The year \u2018invisible\u2019 AI agents will integrate into enterprise hierarchies<\/a><\/strong>\u00a0\u00a0— from venturebeat.com by Taryn Plumb<\/p>\n

In the enterprise of the future, human workers are expected to work closely alongside sophisticated teams of AI agents.<\/p>\n

According to McKinsey, generative AI and other technologies have the potential to automate\u00a060 to 70% of employees\u2019 work. And, already, an\u00a0estimated one-third\u00a0of American workers are using AI in the workplace \u2014 oftentimes unbeknownst to their employers.<\/p>\n

However, experts predict that 2025 will be the year that these so-called\u00a0\u201cinvisible\u201d AI agents\u00a0begin to come out of the shadows and take more of an active role in enterprise operations.<\/p>\n

\u201cAgents will likely fit into enterprise workflows much like specialized members of any given team,\u201d said Naveen Rao, VP of AI at\u00a0Databricks\u00a0and founder and former CEO of\u00a0MosaicAI.<\/p>\n

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State of AI Report 2024 Summary<\/strong> <\/a>— from ai-supremacy.com by Michael Spencer
\nPart I, Consolidation, emergence and adoption.\u00a0<\/em><\/p>\n

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Which AI Image Model Is the Best Speller? Let\u2019s Find Out!<\/strong><\/a>\u00a0— from whytryai.com by Daniel Nest
\nI test 7 image models to find those that can actually write.<\/em><\/p>\n

The contestants
\n<\/strong>I picked 7 participants for today\u2019s challenge:<\/p>\n

    \n
  1. DALL-E 3<\/strong>\u00a0by OpenAI (via\u00a0Microsoft Designer<\/a><\/em>)<\/li>\n
  2. FLUX1.1 [pro]<\/strong>\u00a0by Black Forest Labs (via\u00a0Glif<\/a><\/em>)<\/li>\n
  3. Ideogram 2.0<\/strong>\u00a0by Ideogram (via\u00a0Ideogram<\/a><\/em>)<\/li>\n
  4. Imagen 3<\/strong>\u00a0by Google (via\u00a0Image FX<\/a><\/em>)<\/li>\n
  5. Midjourney 6.1<\/strong>\u00a0by Midjourney (via\u00a0Midjourney<\/a><\/em>)<\/li>\n
  6. Recraft V3<\/strong>\u00a0by Recraft (via\u00a0Recraft<\/a><\/em>)<\/li>\n
  7. Stable Diffusion 3.5 Large<\/strong>\u00a0by Stability AI (via\u00a0Hugging Face<\/a><\/em>)<\/li>\n<\/ol>\n
    \n

    How to get started with AI agents (and do it right)<\/strong><\/a>\u00a0— from venturebeat.com by Taryn Plumb<\/p>\n

    So how can enterprises choose when to adopt third-party models, open source tools or build custom, in-house fine-tuned models? Experts weigh in.<\/p>\n

    \n

    OpenAI, Google and Anthropic Are Struggling to Build More Advanced AI<\/strong><\/a>\u00a0— from bloomberg.com (behind firewall)<\/span>
    \nThree of the leading artificial intelligence companies are seeing diminishing returns from their costly efforts to develop newer models.<\/em><\/p>\n

    \n

    OpenAI and others seek new path to smarter AI as current methods hit limitations<\/strong>\u00a0<\/a>— from reuters.com by Krystal Hu and Anna Tong<\/p>\n

    Summary<\/strong><\/p>\n