The article discusses Taboola’s plans to launch a generative AI advertising assistant called ‘Abby’ by 2024, aiming to compete with tech giants like Google and Facebook in the digital advertising space. Abby will use AI to help marketers create ad campaigns more efficiently by generating ad copy, images, and videos tailored to specific audiences. Taboola believes Abby will save marketers time and money while improving ad performance. The company plans to train Abby on a vast dataset of successful ad campaigns to optimize its recommendations. Taboola’s CEO, Adam Singolda, sees Abby as a way to level the playing field for smaller advertisers who lack the resources of larger companies. However, the article notes concerns about AI’s potential to spread misinformation or biased content in advertising. Taboola aims to address these issues through responsible AI development and human oversight.

The article discusses the phenomenon of ’link rot,’ where links on the internet become broken or outdated over time, leading to the loss of valuable digital information and history. It highlights the fragility of the internet’s infrastructure and the challenges in preserving digital content. Key points include: 1) Billions of links on the internet are already broken, with studies estimating that link rot affects over 70% of online resources cited in scholarly articles. 2) The ephemeral nature of websites, with content constantly being updated or removed, contributes to this issue. 3) Initiatives like the Internet Archive’s ‘Wayback Machine’ aim to archive and preserve web pages, but face limitations in scale and resources. 4) The loss of digital history poses risks for future research, education, and our understanding of the past. 5) Solutions proposed include better archiving practices, legal frameworks for digital preservation, and increased awareness of the issue.

Artificial Intelligence (AI) is rapidly transforming various aspects of our lives, from healthcare and transportation to entertainment and education. The article explores the advancements and potential impacts of AI. Key points include: AI’s ability to process vast amounts of data and identify patterns, leading to breakthroughs in medical diagnosis and drug discovery. AI-powered language models like ChatGPT can engage in human-like conversations and assist with tasks like writing and coding. AI is also driving innovations in autonomous vehicles, improving safety and efficiency. However, concerns are raised about AI’s potential to disrupt job markets and the need for ethical guidelines to prevent biases and ensure responsible development. The article emphasizes the importance of embracing AI while addressing its challenges to harness its full potential for societal benefit.

The article discusses the challenges Tesla faces in achieving its goal of launching a fully self-driving robotaxi service by 2024. Dmitri Dolgov, the cofounder of Waymo, argues that Tesla’s approach of relying solely on data collected from its vehicles’ sensors is insufficient for developing a safe and reliable self-driving system. Dolgov emphasizes the importance of having a diverse dataset that covers various scenarios and edge cases, which is difficult to achieve through Tesla’s data collection method alone. He suggests that Tesla’s approach may work for driver-assistance features but is unlikely to be sufficient for fully autonomous driving. The article also highlights the complexity of developing self-driving technology and the need for rigorous testing and validation to ensure safety.

The article discusses the rise of AI code startups, which are companies that use artificial intelligence to assist with software development tasks such as writing code, debugging, and optimizing performance. It highlights several startups in this space that have raised significant funding from prominent venture capital firms like Andreessen Horowitz. The startups mentioned include Anthropic, which has raised $224 million, Adept, which has raised $350 million, and Codex, which was acquired by Microsoft. The article suggests that these startups are leveraging AI to make software development more efficient and accessible, potentially democratizing the field. It also notes the potential risks and challenges associated with AI-generated code, such as security vulnerabilities and bias. Overall, the article portrays the AI code startup space as a rapidly growing and well-funded area of innovation.

The article discusses Nvidia CEO Jensen Huang’s ambition to have 100 million AI assistants powered by the company’s technology by 2024. Huang believes that AI assistants will become ubiquitous, helping people with various tasks and making their lives easier. He envisions AI assistants being integrated into devices like cars, phones, and home appliances. Nvidia’s AI technology, including its GPUs and software, will power these assistants, enabling them to understand natural language, process data, and provide intelligent responses. The article highlights Nvidia’s focus on developing AI hardware and software solutions for various industries, including automotive, healthcare, and robotics. Huang sees AI assistants as a key part of Nvidia’s future growth strategy, as the demand for intelligent assistants continues to rise across consumer and enterprise markets.

The article discusses the emergence of new players and startups in the field of AI inference, which is the process of using a pre-trained AI model to make predictions or decisions on new data. These companies are developing specialized hardware and software solutions that can perform AI inference tasks more efficiently and at a lower cost compared to traditional cloud providers. The article highlights that by 2024, the prices for cheap AI workloads are expected to drop significantly due to increased competition and innovation in this space. This trend could democratize access to AI capabilities, enabling more businesses and organizations to leverage AI technologies. However, the article also notes that for complex and high-performance AI workloads, cloud providers like Amazon, Google, and Microsoft may still maintain a competitive edge due to their vast resources and expertise.

The 2024 Nobel Prize in Economics was awarded to Daron Acemoglu of MIT, Simon Johnson of MIT, and James A. Robinson of the University of Chicago for their groundbreaking research on the fundamental causes of political and economic development across countries. Their work has shed light on why some nations prosper while others remain mired in poverty. Acemoglu, Johnson, and Robinson developed a framework that emphasizes the importance of inclusive political and economic institutions in promoting sustained economic growth and shared prosperity. They demonstrated how extractive institutions, which concentrate power and wealth in the hands of a few, often lead to economic stagnation and societal unrest. Their research has had a profound impact on our understanding of the complex interplay between politics, economics, and societal progress. The Nobel committee praised their work for providing “a new lens through which to view the wealth and poverty of nations.” Their insights have influenced policymakers worldwide in designing reforms aimed at fostering more inclusive and sustainable development.

According to the article, Nvidia CEO Jensen Huang plans to build a supercomputer called “Grok” by 2024, which will be capable of understanding and explaining its own reasoning, a concept known as “explainable AI” (XAI). Huang aims to rival Elon Musk’s AI ambitions with this project. The article highlights that Grok will be a “time machine” that can learn from data and understand the world better than humans. Huang believes that XAI is crucial for building trust in AI systems and ensuring their safety. The article also mentions that Nvidia is working on a new AI architecture called “Transformer 3D” to power Grok, which will be more efficient and powerful than current AI models. Huang emphasizes the importance of developing AI systems that can explain their decision-making processes, especially in critical areas like healthcare and finance.

The article discusses Nvidia CEO Jensen Huang’s unique approach to job interviews, where he conducts reference checks for candidates as far as two years into the future. Huang believes that hiring the right people is crucial for a company’s success, and he wants to ensure that candidates have the potential for growth and can handle increasing responsibilities over time. During interviews, he asks candidates to provide references not only for their current roles but also for hypothetical future positions they might hold at Nvidia in 2024. This unconventional method allows Huang to gauge a candidate’s long-term potential and assess their ability to adapt and take on greater challenges. The article highlights Huang’s commitment to building a strong team and his willingness to think outside the box when it comes to evaluating talent.