Run prompts locally - lmstudio

• Download https://lmstudio.ai/
• Download mistral model
• Run Prompts Locally

My quick ref tutorial I looked up - Link

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Leadership in Action

Beautiful Lines from the post

• Strategy changes rarely come from a fancy offsite. They come from late-night emails or hallway conversations 
• He never throws anyone under the bus except to take some blame for himself

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Professional Growth Must Come From Personal Growth

Brilliant talk, Loved it. Do not play politics, build on your values.

Thanks for highlighting my quote, Brilliant talk.

Professional Growth Must Come from Personal Growth" was a brilliant talk. It focused on understanding career growth versus values versus visibility. Often, it's a mix of factors that contribute to growth: contribution, visibility, and access to high-value work. Everything involves teamwork. Growth stems from self-centered visibility versus growing as a team; both are traits of a leader, whether selfish or selfless.

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Developing Your Skills in Data Science and AI

You don't need a title to learn/work in data science
You don't need to start with what everyone is recommending.
Focus on a few areas of AI, not the complete landscape.
Seek out mentors to guide you.
Learn by collaborating, solving problems, and asking for help in AI-related issues.
Do not believe that the growth path is the same for everyone; avoid a copycat approach.
Sometimes, you need to work without titles to really excel in your areas of interest.
Experiment / Look for Real-time problem-solving, and proposing solutions
Be resilient setbacks are okay, Pause and find alternate solutions
Consistently seek understanding and clarity. 
Roll up your sleeves, not all the time, but only for meaningful AI work. Remember, you are not a machine. Strive at a consistent pace.
Learn to differentiate Pro AI vs AI Hype and develop intuition to spot it

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Job vs Solopreneur vs Ideas vs Intuition vs Learning

In the corporate world, navigating the hierarchy of influence often poses a challenge, particularly when it comes to balancing the time required to sell personal ideas against completing assigned tasks. Jobs typically compensate us for specific deliverables, not for the incubation or pitching of our innovative ideas.

The process of advancing personal ideas depends heavily on the organizational culture. When there is genuine acceptance and support for innovation, pushing personal concepts becomes not only feasible but also encouraged. However, more often than not, we encounter environments where ideas are welcomed in discussions, but follow-up and implementation fade away, lost to immediate business priorities.

In such scenarios, one may feel compelled to take on a solopreneurial approach. This involves stepping away from the structured organizational roles and exploring the uncertain waters of individual innovation. By adopting the role of a solopreneur, we give ourselves the opportunity to fully develop and test our ideas without the restrictions and influences of corporate agendas.

Living through this uncertainty requires resilience. It isn't merely about having a groundbreaking idea; it's also about having the tenacity to bring that idea to MVP amid fluctuating circumstances. As solopreneurs, we maneuver through diverse challenges, test our limits, and learn invaluable lessons about both our crafts and ourselves.

The Journey is the Experience and the wealth is the Learning 

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Supply Chain Expertise and GenAI Insights

I have worked for Microsoft Xbox supply chain and UPS. Now If I have to add a GenAI lens to my past. Here are my perspectives.

At Microsoft's Xbox division, I managed both forward and reverse supply chain logistics, covering repairs, refurbishment, and warranty services. By integrating GenAI, we can significantly enhance product defect detection, implement targeted product improvements, and streamline supplier communications, elevating overall efficiency and product quality.

At UPS, I collaborated with the team to develop and pitch AI/ML strategies for third-party logistics, focusing on operational efficiencies, visibility, planning, forecasting, and optimization. With the infusion of GenAI, the potential applications could extend to sophisticated chatbots and digital assistants, further refining company policies, fostering broader AI adoption, and enhancing supplier communications.

I am committed to pushing the boundaries of supply chain management with innovative GenAI-driven solutions and look forward to collaborating with startups/product companies in this space. If you are an SMB, have historical data, looking to onboard in AI, Let's connect sivaram[at]phygitalytics.com. 

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Insights, Innovations, and Lessons: Exploring Computer Vision and Generative AI Hybrid solutions

Hoping to share more insights on below Vision + GenAI Journey

1. Captivating Success: Harnessing Vision and Generative AI to Mitigate Food Waste

Unveiling a remarkable deployment where vision technologies, coupled with Generative AI, are being leveraged in a significant initiative to reduce food waste. A partnership between a renowned condiment brand and a leading technology provider exemplifies the powerful application of AI in environmental sustainability.

2. Dual-edged Experiences: Enhancing Product Details and Vision Technology Setbacks

This segment will delve into the mixed outcomes from integrating Generative AI in enriching product detail pages, and the limitations encountered with computer vision technologies. We’ll share an analysis of the decision-making processes in either developing custom vision models alongside Generative AI or opting for off-the-shelf solutions, outlining the key challenges and learnings from both paths.

3. Learning from Setbacks: Challenges in Vision for Skin Care Innovations

Not all ventures yield success, and in the explorative landscape of AI, the application of vision technology for skin care solutions has faced its own set of challenges. This case will reveal the hurdles faced during implementation and the pivotal lessons learned, emphasizing the importance of iterative testing and adaptive strategies in technology application.

Summary:

In wrapping up, the session will highlight the critical takeaways from the successes and setbacks observed in integrating computer vision and Generative AI across different industries. Attendees will gain a nuanced understanding of the practical applications, scalability issues, and strategic decisions crucial for leveraging these cutting-edge technologies effectively.

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Career Perspectives

Few key things that apply to me :)

• Build key relationships by networking and offering something valuable - ideas/playbook / POC.
• Fifth, select challenging projects that promise significant early wins, even if they require extra effort initially.
• Finally, at the end of the month, create a reflective document detailing your observations to better understand and improve your approach.

Ref - CAREER ADVICE: First 30 days as an exec.

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Windows Ad - 1988

 

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Evaluating Common Sense AI Frameworks vs. Business-Driven Realities

The following compares two contrasting approaches: a common sense AI framework that focuses on ethical ideals, and the business-focused reality that often prioritizes profitability and market demands:

People-Centric vs Business-Centric Approach

• Common Sense AI: Prioritizes individuals' needs and well-being.
• Business Reality: Focuses on enhancing business profitability and operations.

Encouraging Learning vs Driving Engagement

• Common Sense AI: Advocates for learning and the personal development of users.
• Business Reality: Strives to increase user engagement which often translates to increased revenue.

Facilitating Connections vs Forming Opinionated Groups

• Common Sense AI: Aims to help people create meaningful connections without bias.
• Business Reality: May encourage the formation of groups based on strong opinions, which can boost platform activity.

Trustworthiness vs Promotion of Varied Information

• Common Sense AI: Committed to being trustworthy in the information it provides or promotes.
• Business Reality: May distribute all types of information, irrespective of accuracy, to cater to diverse user demands.

Privacy Defense vs Utilizing Data

• Common Sense AI: Upholds the privacy of users as a fundamental principle.
• Business Reality: Sometimes utilizes user data without explicit consent to maximize business opportunities.

Safety for Minors vs Conditional Apologies

• Common Sense AI: Ensures the safety of children and teens as a priority.
• Business Reality: Focuses on rectifying issues only when necessary to maintain public image while keeping business priorities intact.

Transparency and Accountability vs Limited Oversight

• Common Sense AI: Maintains high levels of transparency and holds itself accountable to stakeholders.
• Business Reality: Oftentimes finds methods to collaborate or operate without stringent checks, prioritizing flexibility and operational efficiency.

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