AI

OpenAI has unveiled the Model Spec, an evolving document aimed at shaping the behavior of models like ChatGPT and other offerings within the OpenAI API. Continue Reading →

Apple was so excited to release its M4 chip that they put it in the iPad first. According to Apple, "the M4 has a blazing-fast Neural Engine — an IP block in the chip dedicated to the acceleration of AI workloads. It's Apple's most powerful Neural Engine ever, capable of an astounding 38 trillion operations per second — a breathtaking 60x faster than the first Neural Engine in A11 Bionic." Continue Reading →

If you're looking for professionally curated lists of the best dressed stars, Vogue, Vanity Fair, or the New York Times have awesome pictorials. Unsurprisingly, these traditional sources had a bit of competition from deepfakes this year, and several hyper-realistic deepfake images of celebrities like Katy Perry and Rihanna garnered millions of views. Continue Reading →

Where does AI training data come from? You may have been told that Large Language Models (LLMs) are trained on vast amounts of text data scraped from the public web. This is true, but it isn't the whole story. Simply scraping the web and dumping data into a database isn't enough to produce a high-performing LLM. For that, the models need domain-specific knowledge which, at the moment, is mostly done by employing a bunch of subject matter experts to evaluate the data via a process known as annotation. Let's review. Continue Reading →

Will generative AI kill web traffic? It may. AI-powered search tools like perplexity.ai can do 10 minutes of Google searches in about 10 seconds. It cites its sources, gives you a range of GenAI tools to use for output, and (most importantly) does not click on ads. Continue Reading →

Anthropic has unveiled "Team," an enterprise version of its AI chatbot Claude. It's designed to cater to businesses across various sectors such as technology, financial services, and health care. The offering (market priced at $30/per month) includes all of Anthropic's advanced Claude models, admin tools, and the ability to process extensive documents. Continue Reading →

Need to show someone that you are very, very popular? Need social validation to boost your self confidence while out for the evening with your friends? Want 20,000 viewers to interact with you right now? You're just a few taps away. Head over to your favorite app store and download a "fame experience simulator" app. Continue Reading →

Memory allows ChatGPT to act more like a digital assistant than a task-oriented chatbot. Potential uses include remembering formatting preferences, professional/personal context for better answers, and improved recommendations (like what books you’ve previously read). Continue Reading →

Big foundational models like GPT-4, Gemini, Claude, and Llama -- aka large language models or "LLMs" -- are awesome, but they are not experts in your business. They are also available to all of your competitors, so creating competitive advantage requires you to train your subject matter experts to get the most out of the AI and to augment your LLMs to be as relevant to your business as possible. One of the most effective ways to augment an LLM is with the addition of external signals, which are various types of real-world data and information that can be used to influence and improve the performance and relevance of LLMs. Let's take a high-level look at how external signals can transform LLMs, making them more relevant, responsive, and ultimately, more useful. Continue Reading →

In a disturbing exploitation of AI, former Pikesville High School athletic director Dazhon Darien was arrested for allegedly impersonating the school's principal using AI voice synthesis to disseminate false racist and antisemitic statements. The synthetic audio, widely shared on social media, inaccurately portrayed the principal expressing derogatory views about Black students and the Jewish community, triggering widespread condemnation and significant disruptions at the school. Continue Reading →