Welcome Back, Hero!

First of all, I am hosting a FREE webinar on Machine Learning, MLOps, and GenerativeAI roadmap.

Sunday, 20th August, 10:00 AM IST

Register here for FREE: https://topmate.io/himanshuramchandani/493368

How to Leverage Data, Products & AI for Your Business 🏢

Building the Right Data Team

Do you have the right skill sets within the organization to implement AI projects?

The Data Team Conundrum → A data team is the foundation of your AI success.

You have 3 options

• assemble an in-house team,

• outsource to experts,

• or find a balance between the two.

In-House Team

Data Scientists → You need someone who understands

• data intricacies,

• formulate hypotheses,

• and extract insights.

They decipher complex patterns, making data speak a language that influences strategic decisions.

Machine Learning Engineers → You need someone who builds the engines of AI.
They take the insights from data scientists and translate them into algorithms, creating AI models that learn and evolve.

Domain Experts → the storytellers who bridge the gap between raw data and real-world impact.
They understand the industry nuances, ensuring that AI solutions align with business objectives.

→ Bringing in domain experts could complete the puzzle.
→ Hiring a data scientist with manufacturing expertise ensures that data insights translate into actionable supply chain improvements.

Outsource to Experts

• Collaborating with external AI experts who specialize in the manufacturing industry might be more efficient.

• They understand the nuances and can fast-track the project with their domain-specific knowledge.

Imagine the manufacturing company collaborating with an external AI partner. The result could be a faster, more targeted solution that leverages their combined knowledge.

The Balance

While hiring in-house experts can foster long-term growth, partnering with external specialists can accelerate time-to-value.

Striking the right balance depends on the complexity of your project and the resources available.

Need help with AI-Powered Data Engg Solutions, Data Strategy, and Roadmap? → FREE consultation with roadmap, analysis, and data strategy.

Top 2 AI News and Development 📰

1 → Meta's Next Big Open Source AI Dump Will Reportedly Be a Code-Generating Bot

• Meta’s language-centric LlaMA AI will soon find itself in the company of a nerdier, coding wiz brother.

• Meta’s open source strategy has gained clout despite its belated entry into the consumer-end AI race.

2 → How OpenAI Grew

1 Action Tip from Data Experts for Leaders 🎬

Are you Cultivate Diversity while hiring a Data Team?

When assembling your
- data team,
- prioritize diversity in backgrounds,
- skills, and perspectives.

A diverse team brings a rich blend of insights, ensuring that your AI initiatives are not limited by narrow viewpoints.

This diversity fuels innovation and helps your team tackle complex AI challenges with creativity and agility.

All the best!

Investments in AI💲

Wipro → $1 billion

announced that it will invest over $1 billion investment on its artificial intelligence (AI)

For Developers 🧑‍💻

AI code completion tool → Tabnine

Tabnine makes developers more productive by auto-completing their code.

Smart code completion saves a lot of time.

Career & Job in the AI field🚀

Lemon → Senior AI/ML Developer

Patchstack → AI/ML Engineer

Community & Connections🚀

Join 20,000+ data professionals on LinkedIn → Himanshu Ramchandani

GitHub and Resources

Free Data Stuff

Until next Week!

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