Tina Miller’s Post

Communication Pros: This advice is golden from Tina Miller AI is becoming more and more important for organizations. Stay ahead of the game.

AI Interview Mistake #1: not knowing the strengths and weaknesses of multimodal AI. I've been interviewing software engineers to work on our AI infrastructure for some time now, and it's shocking how many interviewees don't know that foundation models can "see and hear" to process images and video. I like to ask how candidates would prepare a RAG dataset that includes JPGs of charts and tables, and most of them jump to an overengineered solution involving building data processing pipelines in-house. It's childs play for a multimodal model to look at a chart, and translate it to something like: ""The chart shows the company's sales revenue from 2018 to 2022. Revenue has steadily increased each year, starting at $5 million in 2018 and reaching $20 million by 2022, representing a 300% increase over the 5 year period. The most significant jump in revenue occurred between 2020 and 2021." There are also more specialized chart-to-text tools available, but they don't offer the same level of control of the output. The best candidates recognize that multimodal models are eye-poppingly expensive at scale, and suggest using them primarily to ship an MVP and get user feedback. The costs can be brought down once the product has traction. The same principles can be applied to all sorts of AI systems: - Use a company like Deepgram to convert raw audio to text for a sales coaching application. Open source alternatives are also available. - When your motion-activated security camera captures a picture/video, send a push notification to the user with a summary. This saves the user from having to go into the app and wait for the image to load. AI models could even let users set their preferences for being notified about things like non-events like the "A man in an Amazon delivery uniform dropped a package off at the door, and immediately left." If you want to work in hot space, you have to do your homework, and stay up-to-date. 💪 -------------- Hi, I'm Miles 👋 During my 10 year career, I was first PM for a startup that was acquired by Salesforce, founded + led AI/ML as ServiceTitan went from $1 billion to $10+ billion, and developed a novel method for finetuning small language models at Google. I'm currently Director of Product (AI) at an ambitious startup- follow for more on AI product management, core AI tech, and interview tips. I'm also taking on a 1-2 clients for AI interview coaching. DM for details.

Article: Job seekers are scrambling to add new AI skills to their LinkedIn profiles as postings mentioning ChatGPT surge Generative AI is taking the world by storm, so it's probably time to update your résumé. The number of job postings mentioning GPT or ChatGPT on LinkedIn has grown 21-fold since the chatbot was released last November, according to a new company report on AI in the workforce that looked at global ... View the article. https://flip.it/i-dfD5

Natural Language Processing, NLP, has not only revolutionized the recruitment game but has also become increasingly relevant in the realm of personal branding. With the rise of digital platforms, individuals now have unprecedented opportunities to shape and promote their brands online. NLP plays a crucial role in helping individuals leverage these platforms effectively to attract opportunities and enhance their professional reputation. One way NLP contributes to personal branding is through sentiment analysis. By analyzing the language and tone used in opinion-piece posts, blog articles, and online interactions, NLP algorithms can assess how individuals are perceived by their audience. This insight allows individuals to tailor their content and messaging to resonate with their target audience, thereby strengthening their personal brand. NLP-powered tools can help individuals identify relevant keywords and topics within their niche or industry. By understanding the language trends and topics that resonate with their audience, individuals can create content that is more engaging and impactful, thus increasing their visibility and influence within their industry. Additionally, NLP can assist individuals in managing their online reputation effectively. By monitoring online mentions, reviews, and feedback, NLP algorithms can alert individuals to any negative sentiment or potential reputational risks. This allows individuals to address issues promptly and proactively manage their online presence, ensuring that their personal brand remains strong and positive. NLP has become an indispensable tool for individuals looking to build and maintain a strong personal brand in today's digital age. By leveraging NLP-powered insights and tools, individuals can effectively craft their online persona, engage with their audience, and attract valuable opportunities that align with their personal and professional goals. If you are ready to harness the power of NLP to elevate your personal brand and unlock new opportunities, do not hesitate to reach out to me at megan@iformat.com. Let us collaborate to craft a compelling online presence that resonates with your audience and propels your career forward. #personalbranding #nlpforbranding #branddevelopment #careerboost #onlinepresence #digitalstrategy #brandingexpert #iformat

Employers surveyed by the World Economic Forum in a May report predict AI will eliminate 83 million jobs by 2027, but create 69 million—a net decrease of 14 million jobs. The LinkedIn report also found that the platform’s users are rapidly adding AI-oriented skills to their profiles, a likely sign job seekers see AI opportunities increasing. The rate at which LinkedIn users added generative AI-related skills, such as natural language processing, classification or “question answering”—the ability to efficiently respond to questions in a way that best prompts AI models—has nearly doubled.

AI Expected to Impact 40% of Jobs Globally by Replacing or Complementing Roles. *IMF Analysis, Jan 2024 Bain echos similar views. Attached is a page from Bain's Labour 2030 report. (Interesting read!!) This sure as heck sounds scary. Yes, but AI is also giving birth to a new wave of career options. As per Indeed – “Searches for generative AI jobs on Indeed have surged nearly 4,000% in the last year”. Roles like LLM Developers/Engineers, AI Data Analysts, AI Product Managers are already in demand. As AI evolves and businesses rush to integrate AI in their workflows, we will also see introduction of new roles. Be ahead of the competition and learn these skills. ->Conversational AI Designer: Merges UX design, copywriting and psychology to craft engaging AI-driven dialogues. -> Prompt Engineer: Designs and refines instructions to guide large language models for efficient & accurate outputs. ->AI Dialogue Developer: Develops the codebase for conversational AI applications, requiring strong programming skills and knowledge of natural language processing (NLP). ->Ethics and Bias Auditor: Assesses AI for ethical integrity, aiming to mitigate biases and ensure fairness in AI operations. ->AI Support Specialist: Offers technical assistance for AI-powered applications. ->AI Content Creator and Editor: Produces and refines AI-generated content. This will be a massive market. ->Compliance and Regulation Specialist: Guarantees AI adherence to sector-specific regulations, essential in areas like healthcare and finance. ->AI Implementation Consultant: Guides businesses in acquiring and integrating AI technologies. ->Voice Interface Designer: Designs voice interactions for AI-integrated devices, requiring expertise in speech recognition and UX design. It’s not all doom and gloom. People who transition to or acquire new AI skills will definitely have an advantage over those who won’t. Want to pivot to a career in AI? I would be happy to help. I am on a mission to mastering AI and will be sharing my learning’s as I go along. 🛎Follow along if you would like to stay updated ♻️ If this might help others 📢Would love to hear your thoughts #ai #automation #aijobs #careers

Research conducted on job postings and professional networking platforms has outlined the key qualities that job seekers are emphasizing and businesses are searching for. As expected, a range of AI skills dominate this lineup🤖🦾 #ai #aiskills #hrtrends #work https://lnkd.in/e4wRU-vu

Quantitative data collection methods (e.g., surveys) often stand at odds with qualitative methods (e.g., interviews). Tools such as surveys enable researchers to collect and analyze data at scale but can constrain the depth and breadth of participants’ answers. On the other hand, tools such as interviews facilitate rich and nuanced data collection, though at the expense of scale. Undoubtedly, the advent of large language models (LLMs) offers unique opportunities to develop new data collection methods. However, should we think of LLMs as survey enhancers? Or should we think of them as automated interviewers? #ethicalai #aiethics #ai #ethics #responsibleai https://lnkd.in/eF592ZyF

✔️The number of job postings mentioning GPT or ChatGPT on LinkedIn has grown 21-fold since the chatbot was released last November. ✔️Postings for AI engineers, in particular, more than doubled between April and June, making it the third-fastest-growing job on the platform. ✔️On Indeed, the number of generative-AI job postings rose by about 50% from July 2022 to July 2023, but the number of generative-AI job searches rose way more — by 12,300% over the same period. ✔️Since January, the number of generative-AI keywords like "ChatGPT" or "prompt engineering" on LinkedIn members’ profiles across the globe has risen an average of 75% month over month. ✔️As of June, the number of members with at least one AI skill was nine times larger than it was in 2016. ✔️The five fastest-growing AI-related skills on members’ profiles are question answering (up 332% year over year), classification (up by 43%), recommender systems (up by 40%), computer vision (up by 32%), and natural language processing (up by 19%). ✔️LinkedIn is expanding its suite of artificial intelligence features, this time adding tools that will generate content for user profiles and job descriptions. #ai #job #skills #promptengineering #chatgpt #chatbot

MYTHS & MISCONCEPTION ON ATS The concept of ATS, their interaction with human recruiters, and their dependence on keyword matching is commonly misunderstood in the following ways: Augmentation, not Replacement: ATS streamlines tasks but lacks human intuition. Therefore it doesn’t replace a human recruiter. Complex Hiring: Recruiters navigate intricacies, especially in specialized roles. Intricacies such as executive placements, specific skill sets, or high-level strategic jobs require human recruiters to navigate these intricacies and ensure the best match for an organization. Decision Making: Final decisions often need human judgment and strategy. Keyword Optimization: Candidates use keywords, and keywords play a significant role in how an ATS filters resumes. However, this doesn’t mean that ATS solely relies on exact matches without considering context, context matters too. Contextual Analysis: ATS evolves to understand synonyms and context. Advanced contextual analysis techniques are being included in modern ATS algorithms. To comprehend the whole context of a candidate’s experience and abilities, they can identify synonyms, related phrases, and contextual significance. For example, when a job advertisement refers to “project management,”, the ATS could also identify phrases like “task coordination” or “team leadership” as pertinent, even in the absence of explicit remarks. NLP Integration: Natural language processing(NLP) enhances understanding beyond keywords. Many ATS systems leverage NLP algorithms to interpret and understand the meaning behind text, enabling them to identify relevant information beyond just keywords. This allows ATS to assess factors like the depth of experience, achievements, and overall suitability of a candidate based on the context provided in their resume. --------------------------------------------------------------------------------- While ATS enhances efficiency, it cannot replace human recruiters. Modern ATS systems are evolving to understand context, moving beyond strict keyword matching. ATS complements, rather than replaces, recruiters!