Generative AI Applications for Professionals

In the past six months, I've been using the OpenAI ChatGPT/LLM AI daily in my professional and personal life. I always find ways how to make my life more and more productive, and I wanted to share the top 8 ways this technology has helped. 1. Copy-check: AI comes in handy when I need to correct my emails at the end of a long day. This ensures quality communication even when I'm fatigued. 2. Writing Formal Emails: For quick responses and formal letters, AI is a lifesaver. As an example, Superhuman new beta for generative AI looks promising, and I can't wait to try Microsoft 365 Copilot and Google Duet! 3. Drafting Formal Letters: Even in Czech! I can prompt the AI with "Write a letter to the state concerning 'X' in Czech and in accordance to Czech law". It reminds me that it's not a lawyer, but it can do full one-page responses and even run the conversation. 4. Marketing Copy: AI proves incredibly useful for creating marketing copy. I provide it with a case study, for example, "https://lnkd.in/eWHsdRPS" and then prompt it for text. 5. Tone of Voice Adaptation: OpenAI can recognize my writing style and rewrite my emails in my voice. The prompt I use is "rewrite this in the style of Jan Rezab". It's even helped me rewrite entire articles for faster reading. 6. Daily Mood Check: I've taken the Google Bard tip to heart and use AI to understand the daily mood on Twitter and what people are discussing. I even ask it to summarize topics I've not been up-to-date with recently. 7. Scanning Agreements: Pasting agreements into AI allows me to quickly scan and find important details. But, it's important to cross-check this info to ensure accuracy. 8. Creating Templated Agreements: AI simplifies creating templated agreements, such as hand-over protocols and confirmations of receivals. It includes all the necessary details, making the process straightforward. I'm curious about your experiences with generative AI tools like ChatGPT and Bard. What is your favorite use-case for ChatGPT? #ChatGPT #AIassistant #ProductivityBoost #AI #Entrepreneurship #Innovation

I've been getting a lot of questions about what L&D leaders can use AI for. The answer? A LOT more than you think. 👇 Generative AI has a lot of use cases, many we don't hear enough about. Here are a few that I've seen L&D leaders explore so far: 🏔 Content Generation 🏔 The most time-consuming parts of the job (think voice overs, subtitles, and getting copy just right) are now sped to lightning speed with AI. An L&D team of one can now do the work of many! 📊 Analyzing Learning Data 📊 The best programs are rooted in quantitative and qualitative research. Before, that meant dozens of call transcripts and surveys, and hours looking for patterns. Gen AI can spot trends super fast. 🤖 Expert Bots 🤖 You can add a new performance consultant or facilitation coach to your team in about as much time as it takes to make a sandwich. Cover your talent gaps or offer learners a robot resource. ⏳ "Just in Time" Learning ⏳ When we talk about bite-sized learning, we're really dreaming of giving folks the exact right resources at the moment of need. AI makes these dreams a reality, offering live skill assessment and feedback. 👑 Personalized Learning 👑 With Gen AI, courses can become designed for each user's learning journey. Imagine curated, unique courses that address each individuals needs, not just what was convenient to put in the LMS. TL;DR 👉 If you're wondering how to hit your learning targets, don't sleep in AI. L&D has capabilities now that we wouldn't have dreamed about five years ago. Interested in learning how we're using AI to transform manager development at Kona? Send me a DM or leave a comment below! This post was inspired by a recent conversation I had with Ross Stevenson and some of the incredible work from Egle Vinauskaite. If you're looking to learn more about AI and L&D, stop reading and give them a follow. What other AI + learning use cases did we miss? Let me know in the comments! #ai #learninganddevelopment #management #hr #peopleops #tech

Not surprisingly, at Mayfield Fund we are seeing a big wave of Gen AI applications; below are 5 use case themes emerging: 1. Content Generation: LLMs producing custom content for marketing, sales, and customer success, and also create multimedia for television, movies, games, and more. 2. Knowledge CoPilots: Offering on-demand expertise for better decision-making, LLMs act as the frontline for customer questions, aiding in knowledge navigation and synthesizing vast information swiftly. 3. Coding CoPilots: More than just interpretation, LLMs generate, refactor, and translate code. This optimizes tasks such as mainframe migration and comprehensive documentation drafting. 4. Coaching CoPilots: Real-time coaching ensuring decision accuracy, post-activity feedback from past interactions, and continuous actionable insights during tasks. 5. RPA Autopilots: LLM-driven robotic process automation that can automate entire job roles. What else are we missing?

The Office of the Governor of California published the report "Benefits and Risks of Generative Artificial Intelligence Report" outlining the potential benefits and #risks that generative #AI could bring to the state's government. While this report was a requirement under California's Executive Order N-12-23, the findings could be applied to any other state, government, or organization using #generativeAI. The report starts providing a comparison between conventional #artificialintelligence and generative AI. Then, it lists six major case uses for the #technology: 1. Improve the performance, capacity, and efficiency of ongoing work, research, and analysis through summarization and classification. By analyzing hundreds of millions of data points simultaneously, GenAI can create comprehensive summaries of any collection of artifacts and also categorize and classify information by topic, format, tone, or theme. 2. Facilitate the design of services and products to improve access to people’s diverse needs, across geography and demography. #GenAI can recommend ways to display complex information in a way that resonates best with various audiences or highlight information from multiple sources that is relevant to an individual person. 3. Improve communications in multiple languages and formats to be more accessible to and inclusive of all residents. 4. Improve operations by optimizing software coding and explaining and categorizing unfamiliar code. 5. Find insights and predict key outcomes in complex datasets to empower and support decision-makers. 6. Optimize resource allocation, maximizing energy efficiency and demand flexibility, and promoting environmentally sustainable policies. The report then considers the #risks presented by #generative AI, including: - AI systems could be inaccurate, unreliable, or create misleading or false information. - New GenAI models trained on self-generated, synthetic #data, could negatively impact model performance through training feedback loops. - Input prompts could push the GenAI model to recommend hazardous decisions (#disinformation, #cybersecurity, warfare, promoting violence or racism). - GenAI tools may also be used by bad actors to access information or attack #systems. - As models are increasingly able to learn and apply human psychology, models could be used to create outputs to influence human beliefs, manipulate people's behaviours, or spread #disinformation. - Governance concerns with open-source AI models third-parties that could host models without transparent safety guardrails. - Difficulty in auditing large volumes of training data for the models and tracing the original citation sources for references within the generated content. - Uncertainty over liability for harmful or misleading content generated by the AI. - Complexity and opaqueness of AI model architectures. - The output of GenAI does not reflect social or cultural nuances of subsets of the population.

Generative AI Is Revolutionizing the Manufacturing Design 💡 💡 Generative AI optimizes manufacturing design by swiftly generating iterations based on specified parameters, accelerating product development and yielding lightweight, efficient designs that might challenge human engineers. Here's how AI is contributing to design optimization: 👉 Generative Design: ⚪ Exploration of Design Space: Generative design algorithms explore a vast design space by considering numerous variables and constraints. This allows for the generation of design alternatives that human designers might not have considered. ⚪ Optimization of Parameters: AI algorithms optimize design parameters such as material usage, weight distribution, and structural integrity. This leads to the creation of designs that are not only efficient but often innovative in ways that may be challenging for traditional design methods. ⚪ Iterative Processes: AI facilitates rapid iteration by quickly generating and evaluating multiple design options. Designers can then focus on refining the most promising concepts, saving time and resources in the design phase. 👉 Performance Prediction: ⚪ Simulation and Analysis: AI enables advanced simulation and analysis of designs. It predicts how different design configurations will perform under various conditions, considering factors like stress, heat, and fluid dynamics. This ensures that the final design meets performance requirements. ⚪ Real-time Feedback: During the design process, AI provides real-time feedback. Designers can instantly see how modifications impact performance, enabling quick and informed decision-making. 👉 Multidisciplinary Optimization: ⚪ Integration of Multiple Disciplines: AI-driven optimization considers multiple disciplines simultaneously, such as mechanical, thermal, and fluid dynamics. This holistic approach ensures that designs are optimized across various parameters. ⚪ Trade-off Analysis: AI helps in analyzing trade-offs between conflicting design objectives. For instance, a design might need to balance factors like weight, cost, and strength. AI assists in finding the optimal compromise among these conflicting requirements. 👉 Customization and Personalization: ⚪ Tailored Solutions: AI allows for the creation of highly customized designs based on specific user requirements. This is particularly relevant in industries like automotive and aerospace, where components can be optimized for individual preferences or operational conditions. 👉 Design Speed: ⚪ Acceleration of Innovation: AI expedites the design process by automating repetitive tasks and handling complex calculations. This acceleration allows for more time to be spent on creative and innovative aspects of design. #DigitalTranformation #Innovation #Industry4 #Automation #Manufacturing ____________________________________ Follow hashtag #neerajmittra to stay connected on Digital Transformation concepts and its practical execution.

𝗨𝘀𝗲 𝗖𝗮𝘀𝗲𝘀 𝗳𝗼𝗿 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗔𝗜 𝗶𝗻 𝗬𝗼𝘂𝗿 𝗝𝗼𝗯 𝗦𝗲𝗮𝗿𝗰𝗵 Generative AI is a valuable resource in your job search — when used properly. Broad AI tools like ChatGPT or Perplexity can be great resources for preliminary drafts of your job search materials. Due to the increasing use of AI, hiring authorities report seeing the exact SAME content from multiple candidates, so do not assume AI is a hands-off approach. For AI-generated content to advance your candidacy, you must be willing to evaluate the output carefully and provide distinctive details. _____________ 📄 𝗖𝗼𝘃𝗲𝗿 𝗟𝗲𝘁𝘁𝗲𝗿𝘀 — AI does better at writing cover letters than any other type of document. You can paste in your anonymized resume (removing company names, titles, locations, and metrics/numbers) and the target job description. It will generate a fair cover letter, but be sure to mix up the phrasing and personalize it with your key value offerings, wins, and EQ. 📄 𝗕𝗶𝗼𝘀 — You can prompt AI with an anonymized resume and it will develop a fair working draft of a biographical narrative. Hone the broad AI output by filling in details about your value offering and impact. 📄 𝗥𝗲𝘀𝘂𝗺𝗲 — Create an outline or rough draft of your resume. Ask for suggested keywords to include in your resume based on your target job description. Do not consider output the finished product. It will require personalization and substantial edits. 📄 𝗟𝗶𝗻𝗸𝗲𝗱𝗜𝗻 — Generate a preliminary version of your About section. If you already have a summary section on your resume, consider entering it as a starting point. You can also ask AI to generate ideas for your headline or content to post. ____________ CAUTION ❌ — Do not enter personal information like your phone number or street address. ❌ — Do not enter company insights, budget / investment / spend, or company information that is not already publicly available. ❌ — DO NOT SUBMIT untouched AI-generated content. It needs to be customized to reflect your voice, personality, and accomplishments. _________ How have you used AI in your job search? Which AI tools do you use? _________ I’m Erica Reckamp ✦ I write career collateral that captivates — Executive, C-Suite & Board Resumes, LinkedIn Profiles & Bios. Visit my profile to Book a Chat, Follow Me, Ring the 🔔, or Connect! #JobSearchAI #Resume #CareerTech #JobSearchLikeaPro #JobSearch

Amid the Money 20/20 hoopla, I forgot to share that I was in Philadelphia the week prior speaking at a private event on a topic that I’ve been asked to talk about more than any other this year: Generative AI in payments. Yes, the hype cycle on this topic is at its highest, yet one of the biggest issues I see right now is that people in the industry don’t know how Generative AI can help them or where they should even start looking. Here are a few random thoughts: 🤖 Despite the hype, it’s still early. If you feel like you’ve missed the boat, don’t stress. We’re only now starting to digest how Generative AI can help us from a practical perspective. ChatGPT and other cool "toys" are great, but now it's time to get down to business. 🤖 Vendors will lead the way in the short term. Companies that have a deep technical bench and a history of developing AI at scale are developing AI solutions in-house now, but most of you will first rely on innovation created by your software vendors. These vendors can range from niche solutions within the fraud prevention space, to customer service platforms, to your database/data warehouse platforms (AWS, Oracle, Snowflake, etc.). 🤖 Don’t try to eat the whole elephant at once. Identify small use cases that may benefit from the application of Generative AI. Sweet-spot use cases for Generative AI in our industry include anomaly detection, large-scale generation of realistic test/training data, automated rule creation, automated chargeback/dispute response, and the optimization/customization of any high-touch outbound customer interaction (support communications, interactive chat, customized marketing, etc.). 🤖 Traditional, predictive AI won’t be going away. Traditional AI and Generative AI will co-exist and will even work in combination with each other.  Your data scientists who have been working on traditional AI will expand their skills to include Generative AI (if they haven't already). 🤖 Keep in mind that as Generative AI technologies evolve, not only do we need to be innovative about how it helps us but we need to be highly defensive about how it’s getting used against us. Criminals have been using Generative AI to sharpen their attack approach and are always a few steps ahead of us. I can talk for hours on these and many more topics related to Generative AI. How are you thinking about it? #ai #generativeai #machinelearning #payments #banking #fintech

"Demystifying Generative AI: Beyond the Hype and Into Practicality" Generative AI, particularly Large Language Models (LLMs), are often (and best) perceived as advanced text completion tools. While they do encompass multimodal capabilities (like images and voice), their core essence remains in text interpretation and generation. My aim here is not to downplay their capabilities but to offer a clear, grounded understanding of their potential and underlying architecture. Imagine a tool that can respond to your random or specific business questions, refine your writing, or translate requirements into functional code. This is where the power of LLMs truly shine. However, it's crucial to remember that these models are not human. They lack human attributes and emotions, operating instead on pure logic and data. One of the key strengths of LLMs is their ability to generate semantically aware content, not just word-for-word matches. This is made possible by their unique underlying technology. LLMs utilize Vector Databases, where fragments of words are encoded into numerical values and positioned in a 3-dimensional space. These positions adjust as the model is trained, reflecting the vast expanse of human knowledge it's fed. But remember, this process is devoid of emotion or contextual understanding. The output is essentially a mathematical mean of human knowledge. This might sound somewhat disheartening, but it's only a limitation if your expectations are misaligned or if you're tackling the wrong problem. When applied correctly, Generative AI can unlock a world of possibilities, enhancing business and personal life in unimaginable ways. From my experience in building with these technologies, I can confidently say that GenAI won't dominate or threaten our existence. Instead, it will be an omnipresent tool, augmenting various aspects of our lives and work. I fully embrace this technology, seeing its potential to revolutionize my profession, achieve my company's objectives, and positively impact my team. And the best part? All of this can be achieved today in safe and secure ways, opening a path for businesses and individuals alike. I'm working to create a policy for an enterprise to use GenAI from a security and privacy standpoint. We all need to think about our approach to protect our businesses and even ourselves. That said, as evident above, I believe it is well worth the thought and effort to make sure we all have access to this technology. #CyberDefense #GenerativeAI #TechInnovation #FutureOfWork #AIForGood #DigitalTransformation

The Transformative Potential of Generative AI for Business A revolution in artificial intelligence is underway - one that allows computers to generate entirely new ideas and content, rather than simply analyze existing information. Known as generative AI, this technology offers immense opportunities for enterprises across sectors. Business leaders need to understand what it is, where it's headed, and how to leverage it for strategic advantage. What Sets Generative AI apart recently was that AI was limited to classifying, categorizing, predicting and optimizing based on patterns in data. But modern generative AI systems like GPT-3 can autonomously create new written content, generate images, produce computer code, and more based on their training data. They achieve this by using neural networks - brain-inspired AI models - to encode information on the vast quantities of text, audio, and visual data they are trained on. This allows them to remix and recombine concepts in innovative ways. Leading generative models have already absorbed much of the knowledge created by humanity so far. Accelerated Pace of Progress New capabilities are being added monthly, taking generative AI from just text to video, audio, software, and beyond. Access is democratizing through cloud APIs from companies like Anthropic, Google, and AWS. The pace of advancement is extremely rapid - wise executives should start building expertise today. Key Business Use Cases The potential business applications are far-ranging: Automated content generation - create on-demand text, graphics, product descriptions Data analysis and insight discovery - surface hidden trends and patterns Product ideation and design - invent new offerings by remixing aspects of past successes. Process optimization - model and simulate complex systems to find efficiencies Forecasting and prediction - anticipate future customer needs and market changes Getting Started with Generative AI Now is the time for firms to run small experiments, learn hands-on, and begin piloting real-world applications. Leadership should drive a multi-year strategy to fully harness generative AI, with an eye toward transforming their business and industry. But start pragmatically - walk before you run. As with all new technologies, there are risks to evaluate regarding data security, model behavior, and ethical use. Governance and monitoring will be imperative. But used responsibly, generative AI may prove to be one of the most significant innovations in business technology yet. The winners will be those who recognize its potential early and act decisively first.

Exploring the Impact of Generative AI with Real-World Tools 🌟 The world of generative AI is not just about potential; it's about practical, everyday applications that are changing the way we work and create. Let's dive into some concrete examples: 🎨 Creative Endeavors: Tools like OpenAI's DALL-E create stunning images from textual descriptions, while Jukebox generates music in various genres. Runway ML offers an accessible platform for artists and creators to experiment with machine learning in their projects. 📝 Content Creation: GPT-3, developed by OpenAI, is a powerhouse in generating human-like text, aiding in everything from writing articles to coding. Bard, Google's conversational chatbot and AI assistant, built on the PaLM2 LLM also helps in generating human like text. Copy.ai and Writesonic are revolutionizing marketing copy and content creation with their AI-driven writing assistants. 👤 Personalized Experiences: The Netflix recommendation engine uses AI to suggest movies and shows based on viewing history, while Spotify's Discover Weekly personalizes music playlists for each user. 📊 Data Analysis and Visualization: Tableau and Microsoft Power BI are integrating AI to help generate more insightful data visualizations and analyses, making complex data more accessible and actionable. 👥 Social Media and Communication: DeepArt and Prisma transform photos into artworks for social media sharing, while Synthesia creates AI-generated avatars for unique video messages. 🌐 Web and Graphic Design: Wix's ADI (Artificial Design Intelligence) and Canva’s Magic Resize use AI to assist in web and graphic design, simplifying the design process and enabling users to create high-quality visuals with ease. As we embrace these tools, generative AI is not just a futuristic concept but a present reality, enhancing our creativity, productivity, and personalization in everyday tasks. The future is here, and it's powered by AI! #GenerativeAI #AIApplications #TechInnovation #AIinEverydayLife