Personalized Learning Strategies

No gradients. No backprop. Just projections — a fundamentally different, mathematically grounded approach to neural network training that scales. Joint work with Manish Krishan Lal, Stefanie Jegelka and Suvrit Sra. 📄 https://lnkd.in/eajcfeH3 Here’s how it works 🧵 • We reformulate training as a 𝗳𝗲𝗮𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝘆 𝗽𝗿𝗼𝗯𝗹𝗲𝗺, not loss minimization. • Each neuron and data point add a constraint. • We then project onto the constraint sets, finding a point that satisfies all constraints = a trained model. Why this is cool: 1. projections are 𝗰𝗵𝗲𝗮𝗽; roughly the cost of a forward pass 2. they can be computed independently across neurons and data points -> 𝗶𝗻𝗵𝗲𝗿𝗲𝗻𝘁 𝗽𝗮𝗿𝗮𝗹𝗹𝗲𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻 3. natural support for 𝗻𝗼𝗻-𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝘁𝗶𝗮𝗯𝗹𝗲 components and 𝗵𝗮𝗿𝗱 𝗰𝗼𝗻𝘀𝘁𝗿𝗮𝗶𝗻𝘁𝘀 We built a whole framework for this: 𝗣𝗝𝗔𝗫 • Think autodiff for projections. • Built on JAX, it inherits hardware acceleration & JIT, with a familiar interface. • We trained MLPs, CNNs, and RNNs with PJAX. • 🔗 https://lnkd.in/ea4pc-SG Looking forward to the community's response! The approach has potential beyond standard training — particularly for tasks with non-differentiable components or local constraints, like 𝗽𝗿𝘂𝗻𝗶𝗻𝗴, 𝗾𝘂𝗮𝗻𝘁𝗶𝘇𝗮𝘁𝗶𝗼𝗻, and 𝘀𝗽𝗮𝗿𝘀𝗲 𝘁𝗿𝗮𝗶𝗻𝗶𝗻𝗴.

When I was in college, I made a different kind of choice. I decided I wouldn’t chase every new course or paid bootcamp. Instead, I’d squeeze the most out of free resources. In the beginning, it felt like chaos, too many tutorials, too many opinions. But after months of trial and error, I built my own roadmap. And that roadmap eventually helped me land my interviews. Here’s what became my pillars of learning: ✅ LeetCode – Practicing DSA here gave me speed and confidence. ✅ Aditya Verma (YouTube) – His DP and recursion playlists saved me countless hours. ✅ Striver’s Graph Series (Raj Vikramaditya) – Turned one of my weakest areas into a strength. ✅ freeCodeCamp – My go-to whenever I wanted to dive into new development skills. ✅ GeeksforGeeks + W3Schools.com – Cleared my basics in C++ and core CS. ✅ ByteByteGo (System Design) – Showed me the bigger picture of scalable systems. ✅ InterviewBit Sheets – My last-mile prep tool for CS subjects. ✅ GateSmashers – Strengthened my fundamentals step by step. This wasn’t just a list, it was my survival kit. I stayed consistent, followed it, and slowly things started to click. If you’re preparing right now, maybe this roadmap helps you find your own. #sde #interviewpreparation #learning #careerjourney #growth #connections #networking LinkedIn LinkedIn News

Stop guessing your next move—let a Personal Development Plan guide your progress. A while back, I mentored a professional named Rahul, who felt he was being repeatedly overlooked for promotions. We conducted a competency mapping session and discovered a key gap in his ability to work cross-functionally and lead diverse teams. 🧩 Rather than feeling discouraged, Rahul saw this as an opportunity. We built a Personal Development Plan (PDP) to close those gaps. By enrolling in relevant courses and taking on cross-departmental projects, Rahul not only improved his skills but also earned the promotion he had been aiming for. 👉 What is a Personal Development Plan (PDP)? A PDP is a roadmap for your career growth, detailing the specific skills you need to develop to advance in your role. Here are the Key Sections every PDP should include: 💢Self-Assessment: Identify your current strengths and areas for improvement based on feedback or a competency mapping session. 💢Goal Setting: Set clear, measurable goals for what you want to achieve in your career (e.g., leadership skills, cross-functional collaboration). 💢Action Plan: Outline the steps you’ll take to close the gaps, such as enrolling in courses, seeking mentorship, or participating in projects. 💢Timeline: Assign deadlines to each action item to track your progress and stay on course. 💢Evaluation: Regularly assess your progress through self-reflection or feedback from peers and supervisors. 💡 Key Action Points: ⚜️Use competency mapping to identify specific skill gaps. ⚜️Develop a Personal Development Plan to close those gaps. ⚜️Engage in practical experiences like cross-functional projects or targeted training. Feeling stuck in your career? Start building your personal development plan today and tackle those skill gaps head-on! #CareerDevelopment #SkillGaps #PersonalDevelopmentPlan #LeadershipSkills #CompetencyMapping #ProfessionalGrowth

Many people believe live trainings work better simply because people can talk to each other face‑to‑face, but that’s not the real reason. In reality, their effectiveness comes from something else entirely, they naturally follow a powerful learning rhythm. Great offline trainings follow one simple logic: action → reflection → understanding → application. This is Kolb’s Cycle. And it’s incredibly powerful. The problem? It was almost impossible to implement it in online learning. That’s why 90% of online courses look like “interactive lectures”: nice slides, videos, quizzes. But that’s content consumption, not transformation. And now - the unexpected twist. For the first time, online learning has caught up with offline experiences. Because AI removed the main barrier: it finally allows learners to get experience, reflection, and practice in a personalized way. Here’s how Kolb’s Cycle looks in modern learning design: 1️⃣ Concrete Experience — action Essence: the learner must do something, live through a situation, face a task — ideally experiencing difficulty or making a mistake that shows their current model doesn’t work. How online: role-based dialogue, scenario simulation. 2️⃣ Reflective Observation — reflection Essence: pause and think — what happened, what actions were taken, and why the result turned out this way. How online: interactive reflection prompts; AI coach provides feedback based on performance and the learner’s own reflections. 3️⃣ Abstract Conceptualisation — understanding Essence: form a new behavioural model — concepts, principles, algorithms that explain how to act more effectively. How online: short video lecture, model breakdown, interactive frameworks, checklists, interactive infographics. 4️⃣ Active Experimentation — application Essence: try the new model in a safe environment and observe the result. How online: AI-based simulation, situational exercise, case-solving with the new approach; AI coach supports and adjusts. The outcome? Online learning stops being “content” and becomes a behaviour tracker. A course becomes a training simulator, not a film. Kolb’s Cycle finally becomes real in digital learning. Do you use this framework? What results have you seen?

Most managers focus on performance once a year. The best managers improve performance daily. After 25 years of managing teams, I've learned, The difference between good and great managers isn't: • Effort • Skill • Tools It's having the right information at the right time. But most people managers work from scattered and stale data: • Random, handwritten notes from 1-on-1s • Performance reviews from 6 months ago • Gut feelings about who's struggling • Occasional frustrated feedback And that's if they can make time to manage at all. Here's where AI comes in. AI won't manage your team.  But it will help you know them. Here's why you need an AI-powered employee dashboard: HIGH-FIDELITY PROFILES | See The Whole Person ↳ Combine resumes, assessments, and feedback into one view ↳ Understand strengths, gaps, and motivations ↳ Predict where they'll thrive and where they'll struggle CONNECTED TO EXPECTATIONS | Align Profile to Performance ↳ Link their capabilities to role requirements ↳ Identify natural fits and development needs ↳ Spot blind spots before they become problems WITH TARGETED DEVELOPMENT | Focus on What Matters Most ↳ Build 90-day plans for 2-3 key capabilities ↳ Adjust based on real data, not assumptions ↳ Track progress with specific milestones INSTANT PATTERN RECOGNITION | Spot What You'd Otherwise Miss ↳ Upload weekly updates, KPIs, and meeting notes ↳ Get early warnings on performance shifts ↳ Let AI identify trends across time PERSONALIZED COACHING | Tailor Your Approach ↳ Get AI-suggested coaching topics for each person ↳ Customize feedback delivery to their profile ↳ Make every 1-on-1 more impactful The AI advantage: It never forgets context.  It spots patterns across months of data.  It grounds your coaching with homework, not guesswork. The 7-step framework: 1. Create high-fidelity employee profiles 2. Connect profiles to role expectations 3. Build targeted development plans 4. Upload ongoing performance data 5. Get AI-suggested coaching 6. Tailor feedback to their profile 7. Track progress and iterate [Get my starter prompts from the carousel below] Better yet: Join our Free Lighting Lesson next week.  And we'll build one together.  In under 30 minutes. November 13th at 1 PM ET: https://lnkd.in/e3h3aRDa A few more tips: • Keep one AI thread per employee for context • Upload data weekly, not just when problems arise • Use AI insights to inform your coaching, not replace it The truth about great management: Most managers react to problems after they happen. Great managers predict and prevent them. Better information leads to better decisions. Better decisions lead to high-performing teams. 📕 Save in case you want to build this out later.  ♻️ Share to help other managers connect with their people. 🔔 Follow Dave Kline for more AI-powered management strategies.

Learning flourishes when students are exposed to a rich tapestry of strategies that activate different parts of the brain and heart. Beyond memorization and review, innovative approaches like peer teaching, role-playing, project-based learning, and multisensory exploration allow learners to engage deeply and authentically. For example, when students teach a concept to classmates, they strengthen their communication, metacognition, and confidence. Role-playing historical events or scientific processes builds empathy, critical thinking, and problem-solving. Project-based learning such as designing a community garden or creating a presentation fosters collaboration, creativity, and real-world application. Multisensory strategies like using manipulatives, visuals, movement, and sound especially benefit neurodiverse learners, enhancing retention, focus, and emotional connection to content. These methods don’t just improve academic outcomes they cultivate lifelong skills like adaptability, initiative, and resilience. When teachers intentionally layer strategies that match students’ strengths and needs, they create classrooms that are inclusive, dynamic, and deeply empowering. #LearningInEveryWay

Picture this: It's 2030. Sarah, an instructional designer, arrives at work. But she's not building courses anymore. Instead, she's orchestrating an AI ecosystem:   • 𝗛𝗲𝗿 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝗔𝗴𝗲𝗻𝘁 analyzes learner patterns overnight, identifying skill gaps traditional assessments miss.   • 𝗛𝗲𝗿 𝗗𝗲𝘀𝗶𝗴𝗻 𝗔𝗴𝗲𝗻𝘁 proposes personalized learning pathways optimized for different preferences and business needs.   • 𝗛𝗲𝗿 𝗖𝗼𝗻𝘁𝗲𝗻𝘁 𝗔𝗴𝗲𝗻𝘁 generates adaptive scenarios and practice opportunities that respond in real-time to performance.   • 𝗛𝗲𝗿 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗔𝗴𝗲𝗻𝘁 measures actual behavior change and business impact, not just completion rates. Sarah's role? 𝗦𝗵𝗲 𝗰𝗼𝗻𝗱𝘂𝗰𝘁𝘀 𝘁𝗵𝗶𝘀 𝗔𝗜 𝗼𝗿𝗰𝗵𝗲𝘀𝘁𝗿𝗮, 𝗺𝗮𝗸𝗶𝗻𝗴 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗰 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻𝘀 𝗮𝗻𝗱 𝗺𝗮𝗶𝗻𝘁𝗮𝗶𝗻𝗶𝗻𝗴 𝗵𝘂𝗺𝗮𝗻 𝗰𝗼𝗻𝗻𝗲𝗰𝘁𝗶𝗼𝗻. The old world is gone. No more rigid courses. No more clunky LMS platforms. No more pre-built curriculums. Instead, there are 𝗶𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝘁 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗲𝗰𝗼𝘀𝘆𝘀𝘁𝗲𝗺𝘀 with conversational AI tutors providing just-in-time coaching, dynamic pathways adapting to performance, and seamless knowledge networks connecting people to expertise exactly when needed. Learning is part of the work, not separate from it. People solve real challenges with AI support, peer collaboration, and adaptive guidance. 𝗧𝗵𝗲 𝗜𝗗𝘀 𝘄𝗵𝗼 𝘁𝗵𝗿𝗶𝘃𝗲 𝘄𝗶𝗹𝗹 𝗹𝗲𝗮𝗿𝗻 𝘁𝗼: - Design human-AI collaboration workflows - Build agent systems that amplify human potential - Create learning ecosystems, not learning objects - Measure real-world impact, not engagement metrics 𝗧𝗵𝗲 𝗾𝘂𝗲𝘀𝘁𝗶𝗼𝗻 𝗶𝘀𝗻'𝘁 𝘄𝗵𝗲𝘁𝗵𝗲𝗿 𝘁𝗵𝗶𝘀 𝗳𝘂𝘁𝘂𝗿𝗲 𝗶𝘀 𝗰𝗼𝗺𝗶𝗻𝗴. 𝗜𝘁'𝘀 𝘄𝗵𝗲𝘁𝗵𝗲𝗿 𝘆𝗼𝘂'𝗹𝗹 𝗯𝗲 𝗹𝗲𝗮𝗱𝗶𝗻𝗴 𝗶𝘁 𝗼𝗿 𝘀𝗰𝗿𝗮𝗺𝗯𝗹𝗶𝗻𝗴 𝘁𝗼 𝗰𝗮𝘁𝗰𝗵 𝘂𝗽. 𝘞𝘩𝘢𝘵'𝘴 𝘰𝘯𝘦 𝘈𝘐 𝘵𝘰𝘰𝘭 𝘺𝘰𝘶 𝘤𝘰𝘶𝘭𝘥 𝘴𝘵𝘢𝘳𝘵 𝘦𝘹𝘱𝘦𝘳𝘪𝘮𝘦𝘯𝘵𝘪𝘯𝘨 𝘸𝘪𝘵𝘩 𝘵𝘩𝘪𝘴 𝘸𝘦𝘦𝘬?

The GenAI landscape is evolving daily. With new models, frameworks, and techniques emerging constantly, it's easy to get lost. This structured learning path ensures you build strong foundations while progressing toward advanced concepts systematically. What's Unique About This Approach? Instead of jumping straight to coding, we focus on understanding core concepts first: • Start with foundational skills (Python, APIs, REST) • Progress through essential concepts (Tokens, Context Windows, Embeddings) • Master modern frameworks (LangChain, LlamaIndex, Semantic Kernel) • Build practical applications using industry-standard tools Technical Deep-Dive: 1. Foundation Layer:    - Token mechanics and prompt engineering    - Context window optimization    - Temperature and model behavior    - Embedding spaces and vector operations 2. Framework Mastery:    - LangChain for chain-of-thought applications    - LlamaIndex for knowledge-intensive tasks    - Vector databases (Pinecone, Weaviate, ChromaDB)    - Custom agent development 3. Advanced Implementation:    - RAG (Retrieval Augmented Generation) systems    - Multi-agent orchestration    - Memory systems and state management    - Custom model fine-tuning 4. Real-World Projects:    From basic Q&A bots to sophisticated systems:    - Document analysis engines    - Knowledge base construction    - Agent swarms and autonomous systems    - Custom LLM implementations Infrastructure & Tools: • Development: VS Code, GitHub, Jupyter • Deployment: Docker, Cloud APIs, FastAPI • Scaling: Kubernetes, MLOps, Monitoring Learning Philosophy: This roadmap isn't just about tools and technologies. It's designed to build: - Strong theoretical foundations - Practical implementation skills - System design capabilities - Production-ready development practices What's Next? I'll be sharing detailed guides for each section of this roadmap. Follow along to: - Get in-depth tutorials - Access code examples - Learn best practices - Stay updated with the latest GenAI developments Whether you're a beginner or an experienced developer, find your entry point and start building. The field of Generative AI is rapidly evolving, and this roadmap will be regularly updated to reflect the latest advancements. What are your thoughts on this roadmap? Which area interests you the most? Let's discuss this in the comments!

Most people think gaming and training simulation have nothing in common. After 20+ years in AAA, and working on real-world simulation projects at Endava, I’ve learned the opposite — the tech and design principles that keep millions of players engaged can transform training platforms too. Lesson 1 — Real-time feedback matters. Instant responses keep players engaged. In training simulations, real-time feedback ensures learners understand consequences and can adjust behavior immediately. Lesson 2 — Storytelling drives learning. Narrative creates emotional connection. Even in simulations, framing exercises as meaningful stories dramatically improves retention and engagement. Lesson 3 — Iterate live, not in isolation. Games evolve via patches. Training platforms benefit from the same agile, user-driven approach — testing, refining, and optimizing exercises in real time. I believe the next big innovations in training simulation will come from leaders willing to borrow from interactive entertainment. What crossover lessons have you seen between gaming and training? #Simulation #Training #AI #Gaming #Innovation

🚨 Breaking: The layoff wave is back, but here's what smart professionals are doing differently this time. Last week alone, massive job cuts hit corporate America: → Amazon: Cutting 14,000 corporate jobs now, with 30,000+ expected soon → UPS: 48,000 positions eliminated this year → Paramount, Target, PwC, Intel, Nestlé: All announcing significant reductions 💡 What's happening: These layoffs span retail, logistics, media, and consulting. The reasons vary from market corrections after over-hiring, changing consumer behavior to operational efficiency drives and of course, AI. But the impact is the same: thousands of talented professionals suddenly navigating an uncertain job market. 🎯 What's actually working for people navigating this: If you're still employed: → Build your "external credibility" now. Write LinkedIn posts, comment on industry topics, get visible in your field before you need to be. → Start having "informational coffee chats" with 2-3 people in adjacent roles monthly, before you need them. → Document your measurable wins quarterly. Not for annual reviews but for the conversation you might need to have in 6 months. If you've been affected: → The 48-hour momentum plan: Update LinkedIn, reach out to 10 warm contacts (not asking for jobs, just letting them know what you're looking for). → Industry-hop strategically: Your skills often transfer better than you think. Target growing sectors, not just familiar ones. → Avoid the "spray and pray" trap: 20 targeted applications with personalized outreach beats 200 generic ones. While most people immediately start applying to the same type of role at similar companies, look at where money is flowing. What problems are businesses trying to solve right now?  Position yourself as someone who solves those specific problems. If you've been laid off, give yourself 24 hours to process.  Then shift into strategic mode. The professionals who bounce back fastest aren't the most qualified, they're the most intentional about their next move. More resource guide in comments ⬇ — 🌿 Re-post to help someone who needs this. 👉 Follow for daily career strategies that actually work in 2025.