Hrishikesh Yadav

Hrishikesh Yadav

Developer Advocate @TwelveLabs | AI & Backend Engineer | @Kaggle 2x Expert | Generative AI Researcher | Ex AI Engineer Shaga

Berlin, Germany

Actions

Hrishikesh Yadav is a Developer Advocate at TwelveLabs, an AI Engineer, and a researcher with experience across diverse AI domains, including multimodal AI, semantic retrieval, knowledge graphs, and agentic systems. Passionate about bridging research and real-world applications, he enjoys building intelligent systems and sharing practical insights to the community.

Area of Expertise

  • Information & Communications Technology

Topics

  • Applied Generative AI
  • Machine Learning
  • Data Science
  • Data Science & AI
  • Big Data Analytics
  • Deep Learning

Exploring the world of AI Agentic Video Intelligence

The talk focuses on providing the exposure to the user about the video understanding and the vision transformer, which would help them to explore more about the usecases. Also, various applications that they can build with the Jockey

- Rise of video understanding, Why now?
- Key applications across industries and various usecases
- Building multimodal intelligence to generate video embeddings with Marengo
- Crafting video embeddings that capture meaning
- Understanding about Agentic Video Intelligence
- Potential of the Agentic Video Intelligence (Jockey)
- The research going on and looking forward in this field
- Q&A and open discussion

Duration would be ideal for 20 Mins

No pre-requisite

Practical Introduction to DiffusionGemma via Google Cloud

The talk focuses on the Autoregressive model architecture and why there is a need for the decision model in this current scenario of the agentic era and what DiffusionGemma provides, so the aim of mine is to introduce and talk about the experimentation of the decision model as DiffusionGemma and Jev and what one can build with this approach.

Also will have the discussion around how one can implement it well using the Google Cloud.

Agenda for the talk

- Understanding of how LLM works (token generation)
- Why need of the "System one" model, why now ?
- Moving from generating text to making decisions
- LLM as Judge, Useful ? but how reliable ?
- Understanding Jev Approach
- Exploring DiffusionGemma (djev)
- Understanding the Jev inDepth
- Experimentation with the DiffusionGemma and Jev
- Best Approach to make use via Google Cloud
- What future looks like
- Q&A

No Pre-requisite needed for the talk, It takes from beginner to intermediate level

AutoML + Cloud: The future of machine learning

Our discussion will focus on why modern applications require AutoML over traditional machine learning. From development to deployment, it helps organisations deploy AIML models into real life. The impact it will have on AIML. In addition to exploring the various AutoML services provided by Google Cloud, the talk will be hands-on about building and deploying the model.

Session Duration: 45 mins

Agenda for the Session:
a. What is Automated Machine Learning (AutoML)
b. Why Machine Learning on Cloud
c. Advantages of AutoML with respect to why companies are shifting towards AutoML
d. Working of AutoML Vision
e. Let's Build AutoML Vision Model on GCP
f. Quiz

Limitation of the Large Language Models (LLMs)

In this talk, we will explore some of the key limitations of LLMs.

Large language models (LLMs) have revolutionized the field of natural language processing, but they are not without their limitations.

Agenda of the Talk -

- Limitation of LLMs -
Hallucinations
Optimization of Context Length
Speed and Cost
Biasedness
Incorporation of Multimodality
LLMs for Other Languages
Ethical Data Generation
Data Privacy
Prompt Injection
- Q&A

Duration - 20 mins

The talk will also discuss the need for retrieval-augmented generation (RAGs) to address some of the limitations of LLMs. RAGs are a type of LLM that are trained to retrieve and synthesize information from a large corpus of text.

The talk will conclude by discussing the future of LLMs and RAGs, and the potential for these technologies to revolutionize the way we interact with system.

Unlock the Data - EDA & AutoEDA

The seasons delves in understanding the process of EDA and also focusing the importance. Also, Hands-on with AutoEDA.

Agenda for Session -

Introduction to Exploratory Data Analysis
Why there is a need of EDA
Importance of EDA in Data Science and ML
Steps involved in EDA
Exploring Data Distributions and Patterns
Handing missing data and outliers
Visualization Techniques for EDA
What is Automated EDA
Techniques for Automated EDA
Various Tools for Automated EDA
Hands on with EDA and AutoEDA (Spaceship Titanic)
Q&A

Duration - 90 mins

World of AutoML on GCP

The session focuses on understanding the AutoML in the GCP and also building the AutoML Vision Model for the classification of the various car damage.

Agenda of the Session -

1. Basics of Cloud Machine Learning
2. Machine Learning Refresher
3. Types of GCP Machine Learning
4. GCP ML Clients
5. Machine Learning API Services
6. Dive into the AutoML
7. Building AutoML Vision Model on GCP
8. Q&A

Session Length: 120 minutes
Mode: Online (LiveStream Youtube)
Youtube: https://www.youtube.com/watch?v=xr5bHV2syhk

How MindsDB is Impacting the Machine Learning World

Mindsdb is an open-source AutoML startup which aims to solve ML modelling & deploying problems with the help of AI in databases. With the help of MindsDB, you can build, train, optimize, and deploy your ML models without the need for other platforms. Predictive Points and Analytics can be fetched with the use of simple queries on the data and ML models 📙. With MindsDB, you can identify patterns, predict trends, and train models using AI and machine learning in databases. Incorporating machine learning into a database speeds up the development of ML.

Session Length: 50 minutes
Mode: Online (LiveStream Youtube)
Youtube: https://www.youtube.com/watch?v=YngjfwJLplA&t=1501s

Hack the Hackathon

The aim of the Hack Hackathon is to have a panel discussion to discussion on the Hackathon, Projects, Experience, Do's and Dont's.

October 2022 Mumbai, India

Hrishikesh Yadav

Developer Advocate @TwelveLabs | AI & Backend Engineer | @Kaggle 2x Expert | Generative AI Researcher | Ex AI Engineer Shaga

Berlin, Germany

Actions

Please note that Sessionize is not responsible for the accuracy or validity of the data provided by speakers. If you suspect this profile to be fake or spam, please let us know.

Jump to top