Emmanuel Ramos is Chief Solutions Officer at OZ Digital Consulting. As technology continues to evolve, new opportunities arise for businesses and professionals. Generative AI is one such advancement that has been rapidly gaining attention in the tech world due to its potential applications and possibilities. It's a type of artificial intelligence (AI) model that uses large language models or image models as part of its framework. By understanding how generative AI works, what it can be used for and some of the challenges with implementing it, CIOs and other tech leaders can have greater insight into this powerful tool set.

In context: Researchers are turning the creative world upside down, exploiting artificial intelligence and machine learning algorithms to turn many tasks into semi-autonomous processes. Nothing is safe from generative AI anymore, not even your local doctor's illegible writing. Years before OpenAI and other organizations started toying with AI to easily generate text, speech, artworks, malware, and videos, machine learning researcher Sean Vasquez was studying a 2013 paper by Google DeepMind's Alex Graves to create "handwriting synthesis" experiments. The experiment is available at Calligrapher.ai, which Hacker News recently rediscovered. The handwriting synthesis behind Calligrapher.ai

AI Has Designed Bacteria-Killing Proteins From Scratch--and They Work Karmela Padavic-Callaghan New Scientist "The AI, called ProGen, works in a similar way to AIs that can generate text. ProGen learned how to generate new proteins by learning the grammar of how amino acids combine to form 280 million existing proteins. Instead of the researchers choosing a topic for the AI to write about, they could specify a group of similar proteins for it to focus on. In this case, they chose a group of proteins with antimicrobial activity." BuzzFeed to Use ChatGPT Creator OpenAI to Help Create Quizzes and Other Content Alexandra Bruell The Wall Street Journal "BuzzFeed Inc. said it would rely on ChatGPT creator OpenAI to enhance its quizzes and personalize some content for its audiences, becoming the latest digital publisher to embrace artificial intelligence. In a memo to staff sent Thursday morning, which was reviewed by The Wall Street Journal, Chief Executive Jonah Peretti said he intends for AI to play a larger role in the company's editorial and business operations this year."

Hey, party people, it's Kyle, continuing to step in for Greg to write Week in Review as he spends time with his newborn. Dunno about y'all, but it's been a week. But because the news never sleeps, I'm rallying with the help of a fourth cup of coffee. I've talked your ears off about it at this point, but I'm under contractual obligation (not really, but still) to mention TechCrunch's upcoming Early Stage 2023 event in Boston on April 20. The one-day summit on startups will include advice and takeaways from top experts, plus opportunities to meet fellow founders and share your own entrepreneurial experiences.

Chinese enterprises increased patent filings for artificial intelligence products rapidly in the past couple of years. The companies holding the most active AI and machine learning patent families are now tech giant Tencent and search engine provider Baidu, ahead of U.S. firm IBM, South Korea's Samsung, Chinese insurance provider Ping An and former AI patent leader Microsoft. The latter company has been seeing one of its major AI investments come to fruition recently, as conversational AI bot ChatGPT by Microsoft partner OpenAI has been making waves. Microsoft swiftly announced another round of funding for OpenAI, rumored to be to the tune of $10 billion. As this chart based on the LexisNexis PatentSight directory shows, Tencent and Baidu became the largest patent owners in machine learning and AI in 2021, each holding more than 9,000 active patent families.

Microsoft is planning to release a new and improved version of their Bing search engine, in collaboration with OpenAI. The new Bing is expected to be much more popular and efficient than the previous version, and could even give Google Search a run for its money. Microsoft has invested a lot of money into the development of this new Bing, and it is hoped that the project will be beneficial for both parties involved.

Generative AI is taking the industry by storm, and startups are scrambling to get a piece of the pie. But where is the real value in this market? We spoke with industry insiders and discovered some surprising insights. From the infrastructure giants reaping the most profits to the app companies struggling to retain users and differentiate themselves. And what about the model providers who started it all?

Schmidt said there are three significant dangers that could result from generative AI, the first being the creation of killer biological viruses. "Viruses turn out to be relatively simple to construct," he said. "An AI system using generative design techniques, plus a database of how biology actually works, and a machine that makes the viruses, which do exist, can start building terrible viruses." Second, bad actors can use generative AI tools to create and target misinformation, which Schmidt said could lead to violence. Lastly, Schmidt said generative AI can be dangerous when its decision-making is faster than humans, particularly in critical situations.

We demonstrate a proof-of-concept of a large language model conducting corporate lobbying related activities. An autoregressive large language model (OpenAI's text-davinci-003) determines if proposed U.S. Congressional bills are relevant to specific public companies and provides explanations and confidence levels. For the bills the model deems as relevant, the model drafts a letter to the sponsor of the bill in an attempt to persuade the congressperson to make changes to the proposed legislation. We use hundreds of novel ground-truth labels of the relevance of a bill to a company to benchmark the performance of the model. It outperforms the baseline of predicting the most common outcome of irrelevance. We also benchmark the performance of the previous OpenAI GPT-3 model (text-davinci-002), which was the state-of-the-art model on many academic natural language tasks until text-davinci-003 was recently released. The performance of text-davinci-002 is worse than the simple baseline. Longer-term, if AI begins to influence law in a manner that is not a direct extension of human intentions, this threatens the critical role that law as information could play in aligning AI with humans. Initially, AI is being used to simply augment human lobbyists for a small portion of their daily tasks. However, firms have an incentive to use less and less human oversight over automated assessments of policy ideas and the written communication to regulatory agencies and Congressional staffers. The core question raised is where to draw the line between human-driven and AI-driven policy influence.

One might assume that when your boss finally comes to tell you that the robots are here to do your job, he won't also point out with enthusiasm that they're going to do it 10 times better than you did. Alas, this was not the case at BuzzFeed. Yesterday, at a virtual all-hands meeting, BuzzFeed CEO Jonah Peretti had some news to discuss about the automated future of media. The brand, known for massively viral stories aggregated from social media and being the most notable progenitor of what some might call clickbait, would begin publishing content generated by artificial-intelligence programs. In other words: Robots would help make BuzzFeed posts. "When you see this work in action it is pretty amazing," Peretti had promised employees in a memo earlier in the day.