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LINKEDIN HIRES AI-POWERED JOB ASSISTANT

AI-POWERED JOB ASSISTANT

Plus, AI attempts to tell the future and fails miserably.



LinkedIn Surpasses 1 Billion Members, Introduces AI Chatbot for Job Seekers

LinkedIn celebrates reaching a milestone of 1 billion members by launching an AI chatbot designed to assist job seekers. The chatbot, powered by OpenAI, offers personalized recommendations and guidance to help users determine if a job opportunity is worth pursuing. Additionally, LinkedIn has introduced other AI tools for Premium members, including automated recruiter messages and AI-generated profile writing suggestions. These initiatives aim to enhance user experience and support LinkedIn’s revenue growth strategy.

FOUNDERS COMMENT: Unfortunately, LinkedIn has doubled down on the job board mentality when fewer and fewer “normal jobs” are to be had. We are rapidly moving towards a task economy where we desperately need marketplaces where we can simply “do business”, and LinkedIn is unfortunately not that place.

The AI Gender Gap: Why Are Fewer Women Using AI Than Men?

A recent survey reveals that while AI usage is growing, there is a significant gender gap when it comes to women embracing AI technology. Women expressed concerns about retaining their voice and personality, lack of technical proficiency, soulless automation, and fears of having their competence questioned. AI experts call for more women to engage with AI tools and work in the sector.

Researchers Develop Facial Recognition AI for Geese, Revolutionizing Wildlife Conservation

Researchers at the Konrad Lorenz Research Center have developed a facial recognition tool using AI that can identify geese based on their beaks. The AI program is about 97% accurate and has important implications for wildlife conservation. Geese are able to recognize each other, which helps facilitate their complex social interactions. This technology allows researchers to study populations, track individuals, and understand social organization among unrelated geese. Similar facial recognition programs have been used for other animals, showcasing the potential of AI for conservation efforts. Citizen scientists can also contribute by photographing geese and sharing their locations with researchers. However, it is important to remember that geese can remember faces too, encouraging respectful interactions with wildlife.

AI Revolutionizes Mineral Exploration for Electric Future

As the world moves towards an electric future, the demand for minerals like cobalt, copper, lithium, and nickel has skyrocketed. To address the increasing need for these minerals, companies are turning to AI to improve the efficiency and success rate of prospecting. KoBold Metals, Earth AI, VerAI, SensOre, and OreFox, along with Rio Tinto, are employing AI algorithms to analyze vast amounts of geological data, enabling them to identify new mineral deposits and underground ore bodies that are invisible using traditional methods.

The Importance of Play in the Age of AI: Beyond Winning and Losing

In this thought-provoking piece, the authors reflect on the impact of AI on various fields, particularly the world of play. They argue that rather than obsessing over whether AI can differentiate between computer-generated and human-produced content, we should focus on the underlying reasons why we engage in these activities. The authors emphasize the value of play in fostering connection, personal growth, and the exploration of deeper truths. Despite AI’s increasing capabilities, they contend that the joy and artistry of human involvement cannot be replicated by machines.

NYU Develops LLMTime, an AI Program for Time Series Forecasting

NYU researchers have developed a new AI program called LLMTime that can predict the next event in a time series, similar to how language models predict the next word in a sentence. Unlike traditional approaches, LLMTime leverages large language models like GPT-3 to handle time series data. By rethinking tokenization, the program achieves accurate predictions in a wide range of time series problems. Despite limitations, LLMTime shows promise for unifying capabilities within a single powerful model and advancing the field of generative AI.

FOUNDERS COMMENT: Interesting technology, however, life doesn’t work that way. This type of analysis can inform decisions but is unable to predict the future as everything that will occur occurs in completely new circumstances: time, place, and people are all different. Expecting the same outcome is, as Einstein would say, insane.

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