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Do GPT 4o lies abound?

Do GPT 4o lies abound?

Is OpenAI (and others) misleading us about the pace of AI improvement? Do GPT 4o lies abound? Is AI excessively hyped, akin to the “NFT moment” that led to a subsequent downturn? Or even the dot com bubble that eventually had to burst? Daily updates on AI developments are a routine part of many AI enthusiasts reading. People tend to vacillate between the idea that we’re approaching AGI (artificial general intelligence) swiftly or hitting a plateau in LLM capabilities. Compelling arguments exist on both sides. This insight explores the notion that AI might be overly hyped. Do GPT 4o lies abound is a question being asked around the web. GPT-4o is used daily by millions of people. Observations by AI evangelists, suggest a decline in GPT-4o’s capabilities since its release. Though anecdotal, the decline is noticeable. For instance, tasks like placing affiliate links in articles are sometimes mishandled by GPT-4o, which previously performed better. The model’s abilities appear to fluctuate over time. Changing tense or tone sometimes barely happens at all and sometimes completely rewrites and changes the original meaning. While GPT-4o is notably fast, its accuracy and comprehension of instructions seem inferior to even GPT-4. OpenAI has a motive to promote GPT-4o over GPT-4 due to electricity cost savings, which are considerable. Emphasizing the speed and downplaying capability might ensure user satisfaction and maintain Plus memberships. Why it suspected AI might be overhyped? Companies have financial incentives to exaggerate AI’s capabilities to attract attention and funding.Instances of companies exaggerating claims during AI demonstrations have been documented (Google, OpenAI, Amazon, etc.).Personal experiences indicate many AI models are slowing down.Despite exponentially increasing model parameters, performance improvements are not proportional (you can’t get more juice from a lemon by squeezing harder).Some argue that AI models are made to sound more human-emulating voice, potentially blurring the line between genuine intelligence and simulated behavior.This insight believes the most advanced AI models surpass current presentations but are not energy-efficient enough for widespread affordability. Consequently, model capabilities are deliberately limited. What say you. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more

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Data Management for AI

Who Are the AI Evangelists?

Who Are the AI Evangelists? What are the responsibilities of an AI evangelist? As a Technology Evangelist, your role entails guiding third-party developers in adopting the most effective strategies for creating innovative AI/ML-driven applications on platforms. You’ll facilitate the adoption of essential tools and frameworks like Core ML, Create ML, Vision, VisionKit, Speech, Natural Language, and others. How do you transition into an AI evangelist? Becoming an internal AI evangelist involves several steps. Firstly, you need to express your interest in AI to your immediate supervisor, emphasizing its significance for the organization. Clearly outline the advantages of AI, such as increased efficiency, data-driven insights, and competitive edge. Through educational efforts and outreach, you’ll encounter employees passionate about ensuring responsible AI creation and usage. With additional training, these individuals can serve as valuable resources, providing guidance in day-to-day discussions or design decisions across the company. Another approach involves integrating ethics reviews into existing AI product evaluations. Conducting these reviews earlier in the development process helps address potential issues proactively, rather than as a last-minute endeavor before launch. This proactive approach minimizes the accumulation of “ethical debt,” which arises when features violate ethical AI principles and require costly adjustments post-release. Implementing formal processes such as consequence scanning workshops, ethics canvases, harms modeling, and community juries, as well as creating documentation like model cards and FactSheets, further enhances ethical considerations throughout the product lifecycle. Who are the pioneers in the AI field? The field of AI owes its development to numerous pioneers whose contributions have been invaluable. Notable figures include Marvin Minsky, John McCarthy, and Alan Turing, whose ideas laid the foundation for today’s AI technologies. Understanding the Voices of AI The emergence of AI has sparked various viewpoints, represented by three distinct camps: evangelists, pessimists, and realists. Evangelists champion AI as a solution to global challenges, while pessimists highlight potential risks and advocate for immediate regulation. Realists acknowledge both the benefits and risks of AI, viewing it as a necessary tool for the future. Navigating the Risks of AI While AI offers significant productivity gains, it also introduces new security risks. For instance, AI-based services may require sharing sensitive data, potentially compromising privacy and intellectual property rights. Additionally, AI-generated code must undergo thorough testing to ensure it is free from malware or unauthorized elements. The surge in AI-driven IoT and generative AI applications further expands the attack surface, necessitating enhanced network security measures. As organizations embrace AI, it’s essential to weigh both its positive and negative impacts. Conducting a comprehensive risk and benefit analysis and establishing clear usage policies are critical steps in leveraging AI effectively. The rise of AI is not merely hype; it represents a transformative force that requires careful consideration to thrive in the modern security landscape. Like2 Related Posts Salesforce Artificial Intelligence Is artificial intelligence integrated into Salesforce? Salesforce Einstein stands as an intelligent layer embedded within the Lightning Platform, bringing robust Read more Salesforce’s Quest for AI for the Masses The software engine, Optimus Prime (not to be confused with the Autobot leader), originated in a basement beneath a West Read more Salesforce Data Studio Data Studio Overview Salesforce Data Studio is Salesforce’s premier solution for audience discovery, data acquisition, and data provisioning, offering access Read more How Travel Companies Are Using Big Data and Analytics In today’s hyper-competitive business world, travel and hospitality consumers have more choices than ever before. With hundreds of hotel chains Read more

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