International students are having a tough time securing a full time job in Tech.

Reasons

1. Market has limited opportunities for entry level junior data/software engineers.

2. People having 0-3 years of workex are competing against job seekers having 8+ years of seasoned experience.

3. Lot of companies have their operations in off-shore, as companies grow the headcount of offshore>>onshore.

Solution :

Build up relevant skillsets, latch on to the newer technologies that will bring you at par with experienced candidates.

Build apps/ai models/data pipelines/dashboards that tracks live data.

People who have secured job has everything to lose and their routine is restricted and have limitied time to be dedicated to learning. You on the other hand have nothing to lose and everything to gain.

Request for that coffee chat.

Take that certification exam.

Attend that quarterly event.

Success is sweeter when its delayed.

AI Engineers can be quite successful in this role without ever training anything.
This is how:

1/ Leveraging pre-trained LLMs: Select and tune existing LLMs for specific tasks. Don't start from scratch

2/ Prompt engineering: Craft effective prompts to optimize LLM performance without model modifications

3/ Implement Modern AI Solution Architectures: Design systems like RAG to enhance LLMs with external knowledge

Developers: The barrier to entry is lower than ever.

Focus on the solution's VALUE and connect AI components like you were assembling Lego! (Credits: Unknown)

All Developers are Now AI Developers

Worldwide, there are 30 million developers, 300,000 ML engineers, and only 30,000 ML researchers.

For those innovating at the very forefront of ML, the references estimate there may only be ~100 researchers in the world who know how to build a GPT-4 or Claude 3-level system.

The good news is that in the face of these talent shortages, tasks that used to require years of fundamental research and sophisticated ML expertise can now be accomplished in days or weeks by mainstream developers building on top of powerful pre-trained language models.

The future belongs to those who can effectively apply existing AI, not just pioneer new AI. Credits - Armand R

Microsoft releases PCs ‘designed for AI, going to be completely new experience!

It will be called "Copilot+ PC”, which uses chips made by Qualcomm rather than Intel, and will have a battery life of 22 hours, Microsoft said, which is slightly ahead of what Apple delivers with its MacBook Pro and MacBook Air. Their new feature called RECALL is going to be very exciting.
https://blogs.microsoft.com/blog/2024/05/20/introducing-copilot-pcs/

OpenAI released GPT-4o?**

It's the JARVIS we all dreamed of.**

It can reason across text, audio, and video in real time. It's extremely versatile, fun to play with and is a step towards a much more natural form of human computer interaction (and even human computer computer interaction)
Checkout: https://openai.com/index/hello-gpt-4o/

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Jensen introduced GPUs like Steve Jobs used to introduce iPhones! ?*
*Nvidia Introduced Blackwell. It's not gonna be the only chip; it’s a platform. —Jensen Huang, CEO, NVIDIA

Blackwell platform for trillion-parameter scale generative AI.

Main features:
- AI Superchip, 208B transistors
- 2nd Gen Transformer Engine: FP4/FP6 Tensor Core
- 5th Generation NVLink: Scales to 576 GPUs
- RAS Engine: 100% In-System Self-Test
- Secure AI: Full Performance Encryption
- Decompression Engine: 800GB/sec

The most powerful GPU in the market. Exciting announcement, from GTC2024.