Voxel51

• Explore, tinker with, and push the boundaries of the latest AI and machine learning technologies to showcase what's possible with open-source tools and frameworks

• Build inspiring prototypes, proof-of-concepts, and example applications that demonstrate creative and impactful uses of AI to the developer community

• Contribute meaningfully to the open source ecosystem by creating and maintaining libraries, tools, datasets, tutorials and guides that enable developers to more easily leverage AI capabilities

• Curate, clean, annotate and publish unique multimodal datasets spanning text, images, audio, video, 3D and other emerging data types to facilitate novel machine learning research and applications

• Create engaging technical blog posts, social media content, videos, and presentations that educate and inspire developers and data scientists to build with AI

•  Collaborate openly with our internal teams and the broader AI/ML community to cross-pollinate ideas, share knowledge, and collectively advance the state-of-the-art

• Evangelize our technology and vision by representing the company at hackathons, conferences, meetups, universities, and other developer-focused events

•  Influence the product roadmap by providing input on the developer experience, uncovering opportunities for new features and improvements based on community feedback and your work

• Continuously learn, experiment with, and provide feedback on beta versions of our latest models and capabilities to help shape the future of our platform

Hacker-in-Residence

LinkedIn

1) Introductory computer vision course for LinkedIn Learning

2) Prompt Engineering with LangChain (releasing March 2024)

3) RetrievalAugemnted Generation with LlamaIndex (releasing Q2 2024)

4) Fine-tuning LLMs with Hugging Face TRL (est release Q3 2024)

5) Text Generation with Hugging Face Transformers (est release Q3 2024)

LinkedIn Learning Instructor

The Artists of Data Science

The ONLY personal growth and development podcast for Data Scientists

Host

Deci AI

Developer Relations Manager

Pachyderm Inc.

Senior Developer Advocate

Comet

ML Developer Advocate

Data Science Dream Job

Principal Data Science Educator

Price Industries

Lead Data Scientist

Bold Commerce

Senior Data Scientist

Emergent BioSolutions

Biostatistician

I create content about deep learning | The DevRel and Deep Learning Dude

Hacking on LLMs, curating multimodal datasets, and writing a book about RAG.

Harpreet Sahota 🥑

sam3 is seriously a step change improvement over sam2

the model is seriously good, glad they brought back text prompts. the automatic segmentation isn't as good as i hoped it to be...but it still works quite well. 

i also got it to output image embeddings and that was cool to visualize in the app

learn more here: https://lnkd.in/gzqJzj6G

🤖 Hacker-in-Residence @ Voxel51| 👨🏽‍💻 AI/ML Engineer | 👷🏽‍♀️ Technical Developer Advocate | Learn. Do. Write. Teach. Repeat.

qwen3vl is literally the best model i've used for video usecases. blows my mind

hosting a virtual event tomorrow about document ai

you may or may not find it interesting, but i guarantee you'll learn something

join me here: https://lnkd.in/dFXPimVc

sony ai released a pretty cool dataset called the fairness human centric image benchmark, super high quality labels

instructions for downloading and parsing the dataset into fiftyone format can be found here: https://lnkd.in/g_VwxJx4

physical AI is top of mind as the next frontier for deep learning. but it'll only succeed if you have good datasets

language models scaled with web-scale text. 

vision models got ImageNet. 

now Voxel51 and NVIDIA are trying to do the same thing for physical AI 

autonomous vehicles, humanoid robots, anything that moves around atoms.

building these systems means millions of hours of testing in high-fidelity sims before you can actually deploy anything. 

petabytes of multimodal sensor data from various modalities

 LiDAR, cameras, radar, IMUs. 

but over 50% of simulations end up completely unusable because the input data is bad.

even small calibration or timing errors between sensors cascade through your neural reconstructions. 

you waste weeks and burn through millions in compute costs before you realize what went wrong.

the new FiftyOne Physical AI Workbench. it integrates with NVIDIA Omniverse and NVIDIA Cosmos and basically sits at the start of your sim pipeline to validate, clean up, and prep your multimodal data before it hits neural reconstruction and synthetic data generation.

what it does:

- automatically audits physical AI inputs across 75+ critical checkpoints

- transforms raw sensor streams into structured, searchable datasets

- triggers accurate neural reconstructions and generates synthetic scene variations

this means fewer wasted compute hours. 

iteration loops go from weeks to hours. 

you build safer, more reliable systems on data you can actually trust.

read more about what we've been building: https://lnkd.in/gC6_zn-X

i recently integrated 4 ocr models into fiftyone as remote zoo models these handle text extraction and document parsing. 

all available as remote zoo sources, you can get started with a few lines of code

different approaches for different needs:

1. mineru-2.5

1.2b params, two-stage strategy: global layout on downsampled image, then fine-grained recognition on native-resolution crops. 

handles headers, footers, lists, code blocks. strong on complex math formulas (mixed chinese-english) and tables (rotated, borderless, partial-border).

good for: documents with complex layouts and mathematical content

https://lnkd.in/dSwimdvp

deepseek-ocr

dual-encoder (sam + clip) for "contextual optical compression." 

outputs structured markdown with bounding boxes. has five resolution modes (tiny/small/base/large/gundam). gundam mode is the default - uses multi-view processing (1024×1024 global + 640×640 patches for details). 

supports custom prompts for specific extraction tasks.

good for: complex pdfs and multi-column layouts where you need structured output

https://lnkd.in/dhJn2h-v

olmocr-2

built on qwen2.5-vl, 7b params. outputs markdown with yaml front matter containing metadata (language, rotation, table/diagram detection). 

converts equations to latex, tables to html. labels figures with markdown syntax. reads documents like a human would.

good for: academic papers and technical documents with equations and structured data

https://lnkd.in/dNdTQYKg

kosmos-2.5

microsoft's 1.37b param multimodal model. two modes: ocr (text with bounding boxes) or markdown generation. automatically optimizes hardware usage (bfloat16 for ampere+, float16 for older gpus, float32 for cpu). handles diverse document types including handwritten text.

good for: general-purpose ocr when you need either coordinates or clean markdown

https://lnkd.in/dCTfGfV8


two modes typical across these models: detection (bounding boxes) and extraction (text output)

i also built/revamped the caption viewer plugin for better text visualization in the app: 

https://lnkd.in/dBebWdga

i've also got two events poppin off for document visual ai:

- nov 6 (tomorrow) with a stellar line up of speakers: https://lnkd.in/gkBEY4_r

- a deep dive into document visual ai with just me: 

https://lnkd.in/dFXPimVc

Open article: Document Visual AI with FiftyOne - November 14, 2025 by voxel51.com

Document Visual AI with FiftyOne - November 14, 2025

hype for this new integration, and proud of the team for shipping it at lightning speed. big ups to Daniel and AdonAI for goin beast mode on this one

🚀 Introducing Physical AI Workbench — integrated with NVIDIA Omniverse NuRec and NVIDIA Cosmos to solve the biggest bottleneck in physical AI.  

More than half of all physical AI simulations fail — not from bad models, but from bad input data. A timestamp off by milliseconds or a calibration drift of a few degrees can cascade through your neural reconstructions, leaving you with unusable results after weeks and millions in wasted compute. 

FiftyOne Physical AI Workbench sits at the start of your simulation pipeline and provides turnkey access to NVIDIA technology to ensure every simulation run begins with trustworthy data: 

✅ Audits 75+ critical checkpoints to ensure every reconstruction starts with validated inputs 
🎯 Enriches raw sensor streams into structured, searchable datasets 
🔗 Integrates directly with NVIDIA Omniverse and NVIDIA Cosmos for high-fidelity reconstruction and synthetic data generation. 

The result: an end-to-end workflow that prevents downstream failures — cutting iteration cycles from weeks to hours and eliminating GPU waste on failed reconstructions. We’re excited to see this workflow power autonomous vehicles NVIDIA DRIVE and robotics NVIDIA Robotics development teams move faster with higher accuracy. 

🔗 Read the full technical breakdown: https://lnkd.in/gTy5-TNF

Christos Magganas

AI Makerspace

Community Builder

Community Build Session Leader: 10/18/23
Christos' Community Creations every other week!  Join our discord https://discord.gg/RzhvYvAwzA

Community Builder

Key Responsibilities:

In-Class Support:

Lead breakout room sessions to facilitate discussions and assignments.
Engage with learners during scheduled online sessions, providing real-time assistance and feedback.
Allocate time for preparing and reviewing course materials.

Offline Support:

Conduct weekly office hours to offer real-time assistance to learners.
Monitor and respond to queries on Discord, ensuring timely and helpful responses.
Participate in testing homework assignments to ensure clarity and effectiveness.

Key Skills:

Leadership and mentorship to motivate and guide learners.
Technical proficiency in tools like OpenAI, Hugging Face, LangChain, LlamaIndex, and cloud platforms.
Effective communication, both online and offline.
Problem-solving abilities to provide solutions to learners' challenges.
Collaboration with AIM staff and other peer supporters to enhance the learning experience.

Benefits:

Engage with a vibrant AI community and interact with industry experts and peers.
Gain hands-on experience in teaching, mentoring, and AI engineering.
Connect with a network of AI practitioners, industry leaders, and potential employers.

Peer Supporter

Stealth Startup

Founding Engineer

Learvo

Led the design of Learvo's mnemonic solutions using LangChain and LlamaIndex as an LLM application architect.
Advanced Generative AI at Learvo, built a PoC for mnemonic learning tools, and collaborated with team on LLM projects as an AI/ML/LLM Engineer.

AI Engineer

Kaleidoscope Data

The AI/ML Research Assistant will work as understudy of the managing partner, collaborating closely with the projects currently in process. There are three projects which will combine NLP, LLM AI, data pipelines, and operationalization of data products. The intention of these projects is to provide a public, visible demonstration of the capability of AI as a tool for marketing Kaleidoscope Data’s AI consulting services, and potentially create a generic framework for applying AI text-oriented business data problems.

The projects are as follows:
1. Production: Operationalize a Reddit Bot which utilizes Retrieval-Augmented
Generation via tooling like LangChain to create effective summaries of subreddit
content, in collaboration with the moderator team of an interested subreddit
2. Analysis: Annotate a document database using OpenAI, using the annotations with
statistical analysis to understand relationships between documents over time
3. Research: Assist with executing research and writing a research paper utilizing
several LLM and embedding-based approaches for a classification task.

Responsibilities:
· Write python and SQL code to manipulate and process data
· Utilize OpenAI API, including writing prompts and processing resulting data
· Conduct statistical and visual analysis of datasets using tools such as pandas,
scikit-learn, matplotlib, jupyter notebook, Tableau, Excel, etc.
· Explain work and analyses to peers and manager using visual aids such as
Google Slides

AI/ML Engineer

FourthBrain

Building a personalized low-latency end-to-end few-shot keyword spotting (FS-KWS) speech recognition model running in real-time on an edge device.

#AWS #Databricks #Audio #SpeechRecognition #Python #PyTorch

Machine Learning Engineer

Cisco

· Collaborated across teams (Data Engineering/Science/Ops) to design and implement a metric framework to streamline workflow.

· Led the integration of MLOps Continuous Monitoring into ML lifecycle on Google Cloud, providing issue detection, insight and resolution.

MLOps is a core function of ML engineering, focused on taking ML models to production, maintaining and monitoring them.

· Created dashboards using Data Studio to gain observability over ML lifecycle by visualizing stability, performance and operational metrics.

· Highlighted current infrastructure gaps that needed to be bridged and laid out an industry best practice roadmap for our use-case specific needs.

Data Scientist

HCL Technologies

· Created dashboards using Data Studio to improve our engineer's time use efficiency. Our insights led to ~10% productivity improvement.
Established and upheld the analytical and reporting set for our team, utilized data to find improvement opportunities and make proposals to managers and stake-holders.

· Took ownership of pipelines and analytical tools, keeping well documented instructions for processes while presenting results to non-technical folks.

· Provided ongoing and ad-hoc analysis on existing reports, writing two or three SQL scripts from scratch for ETL on a daily basis.

Data Analyst

Commercial Energy

· Responsible for analyzing customer usage data to make recommendations to our customers, often reducing their bill by 25% .

· Reported natural gas price volatility for market changes, compared them to historical data and generated visualizations for purchasing decisions daily.

· Built models to automate savings analyses through self-initiative, rigorous cooperative efforts and research, saving ~10 hours of work weekly for each individual involved.

· Led the onboarding and instruction of a strategic savings plan generating thousands of dollars, which I also presented to C-level executives.

Property Management

Establish rental rates, Organize business expenses for 10+ residential/commercial properties, Supervising construction site overseeing ~10+ workers

Manager

🚀 𝐀𝐈/𝐌𝐋 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫 | 𝐈𝐧𝐧𝐨𝐯𝐚𝐭𝐨𝐫 𝐚𝐭 𝐭𝐡𝐞 𝐈𝐧𝐭𝐞𝐫𝐬𝐞𝐜𝐭𝐢𝐨𝐧 𝐨𝐟 𝐀𝐈 𝐚𝐧𝐝 𝐓𝐞𝐜𝐡𝐧𝐨-𝐏𝐡𝐢𝐥𝐚𝐧𝐭𝐡𝐫𝐨𝐩𝐲

🎓 𝐄𝐝𝐮𝐜𝐚𝐭𝐢𝐨𝐧:
- 𝐀𝐈 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫, 𝐋𝐋𝐌 𝐎𝐩𝐬 & 𝐄𝐧𝐠 @ AI Makerspace 🏗️🚢📢
- 𝐌𝐋 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫 @ FourthBrain, specializing in real-time speech recognition models on edge devices.
- 𝗠.𝗦., 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 @ CU Boulder (paused TBD) 🦬
- 𝗕.𝗦., 𝗔𝗰𝘁𝘂𝗮𝗿𝗶𝗮𝗹 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 @ UC Santa Barbara 🤠💙💛

💼 𝗖𝘂𝗿𝗿𝗲𝗻𝘁 𝗪𝗼𝗿𝗸 𝗮𝘁 𝗔𝗜 𝗠𝗮𝗸𝗲𝗿𝘀𝗽𝗮𝗰𝗲:
- 𝗖𝗼𝗺𝗺𝘂𝗻𝗶𝘁𝘆 𝗕𝘂𝗶𝗹𝗱𝗲𝗿: Facilitating "Christos' Creates" bi-weekly; fostering a dynamic AI and ML community on our Discord server. Utilizing expertise in ML, LLMs, and AI to enrich community discussions and learning, including serving as Peer Supporter for the AI Engineering cohort.
- 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗲𝗱 𝗖𝗼𝗻𝘀𝘂𝗹𝘁𝗮𝗻𝘁: Proficient in leveraging LLMs for product development, creating intricate apps using LangChain and LlamaIndex frameworks, contributing to open-source LLM projects, and collaborating on end-to-end Generative AI applications.

🛠 𝗦𝗸𝗶𝗹𝗹𝘀:
- Proficient in 𝗣𝘆𝘁𝗵𝗼𝗻, 𝗦𝗤𝗟, and data manipulation tools.
- Experienced in deploying 𝗟𝗟𝗠 𝗮𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀, teaching new structures to LLMs, and developing responsive Q&A tools.
- Skilled in 𝗠𝗟𝗢𝗽𝘀, 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲, and the operationalization of AI technologies.
- Advanced proficiency in 𝗡𝗟𝗣, 𝐀𝐮𝐝𝐢𝐨 𝐏𝐫𝐨𝐜𝐞𝐬𝐬𝐢𝐧𝐠, and 𝗗𝗲𝗲𝗽 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 with tools such as 𝗧𝗲𝗻𝘀𝗼𝗿𝗙𝗹𝗼𝘄, 𝗣𝘆𝗧𝗼𝗿𝗰𝗵, and 𝗚𝗖𝗣/𝗔𝗪𝗦 platforms.
- Strong 𝗽𝗿𝗼𝗷𝗲𝗰𝘁 𝗺𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁, 𝗹𝗲𝗮𝗱𝗲𝗿𝘀𝗵𝗶𝗽, 𝗮𝗻𝗱 𝗰𝗼𝗺𝗺𝘂𝗻𝗶𝗰𝗮𝘁𝗶𝗼𝗻 skills; adept at fostering 𝗰𝗿𝗲𝗮𝘁𝗶𝘃𝗶𝘁𝘆 𝗮𝗻𝗱 𝗰𝗼𝗹𝗹𝗮𝗯𝗼𝗿𝗮𝘁𝗶𝗼𝗻 in technology teams.

🌟 𝗩𝗮𝗹𝘂𝗲𝘀 𝗮𝗻𝗱 𝗚𝗼𝗮𝗹𝘀:
- Passionate about leveraging AI and ML to address societal challenges, aiming to join a mission-driven team that encourages learning, growth, and innovation.
- Focused on community building and knowledge sharing, contributing as a volunteer and consultant to foster growth and collaborative problem-solving.
- Aspiring to use my expertise for techno-philanthropic ventures, driving advancements that benefit humanity.

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The Battle

Harpreet Sahota 🥑

Christos Magganas

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The Battle

Harpreet Sahota 🥑

Christos Magganas

Followers

Posts

Engagements

Likes

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Harpreet Sahota 🥑's LinkedIn Performance

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