The BIG Difference Between The Mindset of American And European Tech Workers

Belief in growth is the primary difference between Software Engineers in the USA vs Europe. Many American tech workers understand that their equity options can be huge if their company succeeds. However, European tech workers are often more geeky and "pure" as engineers.

Lessons From Crossing $10M ARR (Entirely Inbound)

How did James achieve viral growth as a product analytics company? How does the open-core model of the company help them grow? How deliberate were they with growth?

Why You Should Be Racist Toward European VCs (An Argument For YC)

James lists his location as San Francisco Bay Area simply to avoid the horrible European VCs (Venture Capitalists).

Why There Will Be Fewer Product Managers In Tech

The trend is clear: engineers will have increasingly more power in the workplace, and the number of PMs needed for 'alignment' will diminish.

The Mistake Engineers Make During The Reverse Interview

Too many engineers don't think critcally about the impact of the last 5-10 minutes of an interview.

The Really Important Job Interview Questions Engineers Should Ask (But Don't)

Basic questions that engineers should ask when interviewing at any company. 

From the Posthog blog: <https://posthog.com/founders/what-to-ask-in-interviews>

Paper Reading: The Future of Large Language Model Pre-training is Federated

Session led by [Mike A](https://www.linkedin.com/in/malik-mike-a-32b63818b/)

Is the future of model pre-training decentralized?

Join us for a captivating session as we explore the cutting-edge breakthrough of federated learning in language model pre-training, featuring an in-depth discussion of the "The Future of Large Language Model Pre-training is Federated" paper!

This paper reading event will shed light on how federated learning (FL) could be set to revolutionize the training of large language models (LLMs). Discover how FL could mobilize vast, underutilized data and computational resources from across the globe, enabling large-scale collaboration and democratizing the pre-training of LLMs. Learn about the innovative approach that allows organizations, and hopefully, soon individuals, to collectively train LLMs using limited resources while matching or even surpassing the performance of traditional centralized models!

This event is a must-attend for AI researchers, software developers, data scientists, and tech enthusiasts eager to grasp the future of LLM pre-training and its implications for AI advancements. Whether you're interested in scaling AI models, leveraging federated learning for collaborative training, or simply curious about the next big thing in AI technology, this paper reading offers invaluable insights and discussions on some of the latest AI research.

Mark your calendars and join us for an exciting hour of "Federated Learning: The Future of Large Language Model Pre-training" exploration!\
\
**Reference Links:**\
[https://flower.ai/\
https://github.com/adap/flower](https://flower.ai/￼https://github.com/adap/flower)

Paper Reading: Beyond Next-Token Prediction: Enhancing Language Models with Multi-Token Outputs

Session led by: [Lucia Mocz](https://www.linkedin.com/in/lucia-mocz-ph-d-35a98a1b6/)

In this talk, we will look at groundbreaking research on advancing the training of large language models. Traditional models like GPT and Llama rely on next-token prediction, which can be expensive and time-consuming, but this research suggests a more efficient approach: multi-token prediction.

**Key Highlights:**

- **Enhanced Sample Efficiency**: Training models to predict multiple future tokens at once increases sample efficiency, leading to significant improvements in downstream capabilities.
- **Innovative Architecture**: By employing n independent output heads on a shared model trunk, better performance with no additional training time can be achieved.
- **Superior Performance**: 13B parameter models outperform strong baselines on generative benchmarks, solving 12% more problems on HumanEval and 17% more on MBPP.
- **Algorithmic Reasoning**: Multi-token prediction fosters the development of induction heads and enhances algorithmic reasoning capabilities.
- **Faster Inference**: Models trained with 4-token prediction are up to 3 times faster during inference, even with large batch sizes.

Join us to explore how multi-token prediction can revolutionize language model training and performance, especially for coding and natural language tasks.

Don't miss this opportunity to learn about the future of language model training and its practical applications!\
\
Paper: [**https://arxiv.org/pdf/2404.19737**](https://arxiv.org/pdf/2404.19737)

Maximizing a Severance Package 9/9 - Summary

Watch Ethan's other course on Taro about [Managing Up](https://www.jointaro.com/course/managing-up-build-effective-relationships-with-your-boss/) and [The Growth And Promotion Recipe](https://www.jointaro.com/course/the-growth-and-promotion-recipe-magic-loop/)

Follow ups:

- Connect with [Ethan on LinkedIn](https://www.linkedin.com/in/ethanevansvp/)
- Taro members get a discount to join [**Ethan's Level Up community**](https://levelupwithethanevans.substack.com/taro25)

Maximizing a Severance Package 8/9 - Can You Sue?

- Connect with [Ethan on LinkedIn](https://www.linkedin.com/in/ethanevansvp/)
- Taro members get a discount to join [**Ethan's Level Up community**](https://levelupwithethanevans.substack.com/taro25)

Maximizing a Severance Package 7/9 - Common Asks and Gives

Maximizing a Severance Package 6/9 - The Mind of the Manager

Maximizing a Severance Package 5/9 - Preparing Your Case

Let's talk about how to prepare your case to maximize your severance package.

- Connect with [Ethan on LinkedIn](https://www.linkedin.com/in/ethanevansvp/)
- Taro members get a discount to join [**Ethan's Level Up community**](https://levelupwithethanevans.substack.com/taro25)

Maximizing a Severance Package 4/9 - Never Accept on the Spot

During a termination, don't sign anything on the spot. **Buy time.** Buy time to do your research, to prepare, and to come back and negotiate.

- Connect with [**Ethan on LinkedIn**](https://www.linkedin.com/in/ethanevansvp/)
- Taro members get a discount to join [**Ethan's Level Up community**](https://levelupwithethanevans.substack.com/taro25)

Maximizing a Severance Package 3/9 - Termination Circumstances

Let's talk about the different circumstances where you may need a package or to try and get a severance from a company.

- Connect with [**Ethan on LinkedIn**](https://www.linkedin.com/in/ethanevansvp/)
- Taro members get a discount to join [**Ethan's Level Up community**](https://levelupwithethanevans.substack.com/taro25)

Maximizing a Severance Package 2/9 - The Law

There are lots of laws around termination of employment, and they vary widely by country. Let's talk about what companies must (or must not) do when doing a Reduction in Force (RIF) or layoff.

- Connect with [**Ethan on LinkedIn**](https://www.linkedin.com/in/ethanevansvp/)
- Taro members get a discount to join [**Ethan's Level Up community**](https://levelupwithethanevans.substack.com/taro25)

Maximizing a Severance Package 1/9 - Introduction

You are being laid off, getting fired, or just want to move on - learn how to get the best package as a part of your transition out of your company.

What's In the Course:

- The Law
- Termination Circumstances
- Never Accept on the Spot
- Preparing Your Case
- The Mind of the Manager
- Common Asks and Gives
- Can You Sue?
- Summary

##### [**Ethan Evans**](https://www.linkedin.com/in/ethanevansvp/) is a retired Amazon Vice President, now sharing his leadership expertise. Ethan has reviewed over 10,000 resumes in his career, conducted more than 2500 interviews, and been part of several layoffs. These career growth courses are developed from his own knowledge and input from his extensive network of fellow coaches and executives.

- Connect with [**Ethan on LinkedIn**](https://www.linkedin.com/in/ethanevansvp/)
- Taro members get a discount to join [**Ethan's Level Up community**](https://levelupwithethanevans.substack.com/taro25)

[Paper Reading] Netflix : Query Facet Mapping and its Applications in Streaming Services

Led by [Dharin Shah](https://www.linkedin.com/in/dharinshah/)

For a Taro Premium discount from Dharin, use his referral link here: <https://www.jointaro.com/r/dharins694/>

This deep-dive goes through how Netflix built their internal query to facet mapping layer to have better understand intent of the query. For example - matching 'anim' to 'Demon Slayer' as higher rank than perhaps 'animal planet'. In this session we dive into the white paper released by Netflix around their implementation.

Link to Paper: [**https://dl.acm.org/doi/pdf/10.1145/3477495.3536330**](https://dl.acm.org/doi/pdf/10.1145/3477495.3536330)

[Timeless Career Advice] Junior to Senior Engineer (And Beyond)

Congratulations, you made it to the end of the course, **Timeless Career Advice for Software Engineers**!

Bonus documents available to you: 

- [Timeless Advice for SWE Careers \[Cheat Sheet\]](https://drive.google.com/file/d/1gzvPMib9IM1yRdz7qiTIKtcEZFIF0GyQ/view?usp=drive_link)
- [Promotion Guide \[Cheat Sheet\]](https://drive.google.com/file/d/1d8tq9EEL7ZeXKMMf4SFC9zjrOZT7-0nc/view?usp=drive_link)
- [Louie's Income Progression in Tech](https://drive.google.com/file/d/1OKtp67v8V0k52GXnQ9yYsn2n-0zb7dIQ/view?usp=drive_link)

Connect with Louie:

- SmallBets community: [**https://smallbets.com/?utm_source=taro**](https://smallbets.com/?utm_source=taro)
- Twitter: [**https://twitter.com/LBacaj**](https://twitter.com/LBacaj)
- Newsletter: [**https://newsletter.memesmotivations.com/**](https://newsletter.memesmotivations.com/)

Feel free to share any feedback on this course with us at [**team@jointaro.com**](mailto:team@jointaro.com).

Share + get support on the Taro forum: [**joinTaro.com/questions/create/**](http://joinTaro.com/questions/create/)

Tech Career Growth Videos

Our instructional videos provide software engineers with insights needed for career growth. Masterclasses go incredibly in-depth on a specific tech topic while case studies are real examples from established engineering leaders.