🦾Jepson Taylor

VEOX

VEOX Inc is revolutionizing the AI industry by creating an AI-driven algorithm factory, compressing decades of progress into moments. Our technology automates AI science research, continuously improving algorithm efficiency and outperforming human-made algorithms. VEOX is not just building another AI company; we're catalyzing an explosion of technological advancements that will reshape the entire tech landscape. Join us in accelerating intelligence beyond human limits and leading the next wave of AI breakthroughs.

CEO/founder VEOX

Artificial Intelligence Masterclass, NYU - Intellibus

FYI, I’ll be co-leading an AI Master Class for about 20 senior leaders at NYU’s School of Professional Studies in September and October!  We have a fantastic team of expert AI panelists too, and I’d love to have you join the program. If you’re keen then drop me a note and I’ll make sure a spot is saved for you.  Also, feel free to send this link onto others who will benefit from joining. This course will be the #1 AI course in the US for senior leaders and will change the way you think about AI and how we tackle its opportunities and threats. A big part of this course is the close collaboration between industry and academia. More info here: https://www.aimasterclass.com/

Contributing Faculty

AtomicSoul.ai

I love being the host for the Atomic Soul Podcast where I explore the very things driving humanity forward. This isn’t your average “AI is taking over our civilization” show - it’s something much more rare that’s sure to make you reevaluate your perspective on controversial topics. Each week we’ll hear from the world’s most interesting people, like corporate giant execs and people bending the mold. It’s at this very intersection of tech and the brain where we expand our consciousness.

Podcast Host

Dataiku

I will provide straightforward industry perspectives and insights, thought leadership on the future of AI, and share the stories and best practices of Dataiku’s growing enterprise customers. I will help accelerate the company’s strong recent momentum, including: 
Over 500 customers with 150+ on the Forbes Global 2000 list
95% customer retention rate with Forbes Global 2000 customers 
Industry recognition includes being named to the Forbes Cloud 100 and Forbes AI 50 lists, top 10 in the Data50, and Snowflake’s ML/AI partner of the year.  
Certification as a Great Place to Work, with 94% of Dataikers saying the company is a great place to work (compared to 57% of employees in a typical U.S.-based company)

You can’t have fun if the fundamentals aren’t working and I was impressed with Dataiku’s growth, enterprise customer count, customer satisfaction, and one collaborative platform. 

I want to work for a market leader and believe that Dataiku is indeed the leader that industry analysts and 500+ customers say they are and I want to invest my life force into this company. 

I am very excited about the next year, and my excitement has only continued to increase since joining. This company has the soul I was seeking.

Read more about my WHY here https://blog.dataiku.com/ben-taylor

Chief AI Strategist

DataRobot

As Chief AI Strategist at DataRobot, I work closely with our innovation team, marketing, sales, and product to ensure innovation is aligned with our product roadmap/strategy. I also help nurture strategic partnerships for the innovation team, can we combine like-minded visionaries to accelerate the future? Can we inspire the next generation by combining world-class innovation with brilliant storytelling? I love working with brilliant technologists and amplifying them with genius creatives. Magic happens between these two types of experts. Some of that work was showcased with our 10,000 cast piece which ended up being nominated for a Webby award. Very excited about what we have in the pipeline this year.

Artificial intelligence is already changing our world for the better. Unfortunately, too many homegrown projects are failing giving the rest of the industry a bad rap. Too many executives are naive to the opportunity. The gap of "do-ability" isn't being crossed in the mind of the business executive. AI should inspire, it should transform, everyone should wake up in the morning excited about what AI could do to automate their business and lift our society to new innovative heights.

Chief AI Evangelist

Zeff

co-founder, Chief AI Officer

Working crazy hours to deliver the world's best machine and deep learning to product companies with the least amount of effort. Our goal was to be easiest to use, but surprisingly we are winning on scalability, accuracy, and implementation time. If you need any machine learning in 2017/2018 reach out to see if you are a fit for our current offering. Great press to come.

co-founder & Chief Data Officer

HireVue

Building out HireVue's data science team with the talent needed to execute on our technical data roadmap. We currently have one of the best deep learning teams in the state and by next year it could be one of the top 10 deep learning teams in the country. I love the work we are doing, the opportunity we have, and the success we are seeing. Working with brilliant people is critical to job satisfaction and we have that at HireVue.

Chief Data Scientist

Is it possible to take something as unstructured and complicated as a digital interview and predict the quality of the candidate response? The answer is yes! Imagine what you can do with 100,000x more data than a resume. Leading HireVue's data science team to success on algorithm development for the HireVue insights IRIS product, a new data frontier for sure.

Principal Data Scientist

Metaheuristic Solutions LLC

Metaheuristic Solutions is a optimization consulting company with the world's leading metaheuristic optimization algorithm, the x algorithm. The new algorithm was developed by Ben Taylor and was made available in 2011.

Founder/CTO

IM Flash Technologies

Using Matlab, R, and Julia to develop multivariate and single variate models and analysis (MVA/UVA) for tool fault detection. These models are then used to shut down tools used in the semiconductor manufacturing process, notify stake holders, and mark up lots for real-time detection analysis (RDA). Projects also include building complex yield models from tool data and automating alarm rule setup as well as fab wide tool fingerprinting to identify rogue behavior even if alarms are not present.

I am also very busy on the web app side building PHP/Mysql wrappers to give engineers access to big data solutions. Hoping to switch soon to python/django/postgres. Also using custom built SQL queuing system that I designed on the backend to manage user loading for job requests.

Senior Data Scientist, Fault Detection

launchup.org

observer

I build stuff that doesn’t exist, an AI explorer. 
Unfortunately I have too many connections so please follow me instead. 

人工智能 (Chinese)
人工知能 (Japanese)
कृत्रिम बुद्धिमत्ता (hindi)
الذكاء الاصطناعي (Standard Arabic)
কৃত্রিম বুদ্ধিমত্তা (Bengali)
искусственный интеллект (Russian)

I watch the watchers, I direct the learners. 

I am passionate about machine learning. My life's mission is to further the boundaries of what is possible with data science. I spend as much time as I can working with deep learning, NLP, and all forms of data science. I currently have a passion project I am managing where I am combining the power of genetic programming with deep learning to automate network design. I think there is a trend happening in data science where human expertise and creativity are being replaced by powerful new methods (i.e. deep learning, big data). 

I am most well known for my machine learning work with the data science community and with HireVue. With the community, I enjoy posting opinions on jobs and tutorials on ML methods. I also enjoy speaking and presenting to all types of audiences. 

I've enjoyed working across engineering, product, sales, marketing, and customer success. This wider POV has helped shape the way I think about innovation, from the innovation farm to the customer's table ;)

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.

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

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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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