“As the head of a newly formed organization within the new GE Digital business, Yonatan created a cross-functional team of highly motivated people and successfully launched innovative initiatives to drive the development of the Predix platform and provide new solutions to Fortune 500 industrial companies. ”
Sign in to view Yonatan’s full profile
Welcome back
By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy.
New to LinkedIn? Join now
or
By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy.
New to LinkedIn? Join now
Los Angeles, California, United States
Contact Info
Sign in to view Yonatan’s full profile
Welcome back
By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy.
New to LinkedIn? Join now
or
By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy.
New to LinkedIn? Join now
3K followers
500+ connections
Sign in to view Yonatan’s full profile
Welcome back
By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy.
New to LinkedIn? Join now
or
By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy.
New to LinkedIn? Join now
View mutual connections with Yonatan
Welcome back
By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy.
New to LinkedIn? Join now
or
By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy.
New to LinkedIn? Join now
View mutual connections with Yonatan
Welcome back
By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy.
New to LinkedIn? Join now
or
By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy.
New to LinkedIn? Join now
Sign in to view Yonatan’s full profile
Welcome back
By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy.
New to LinkedIn? Join now
or
By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy.
New to LinkedIn? Join now
Recommendations received
2 people have recommended Yonatan
Join now to viewView Yonatan’s full profile
Sign in
Stay updated on your professional world
By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy.
New to LinkedIn? Join now
Other similar profiles
-
Dann Wilkens
San Francisco Bay AreaConnect -
Jose Lazares
San Francisco Bay AreaConnect -
Sanjay Poonen
Los Altos, CAConnect -
Gytis Barzdukas
San Jose, CAConnect -
Rami Qasem
Dubai, United Arab EmiratesConnect -
John Krachenfels
United StatesConnect -
Suparna Pal
San Francisco Bay AreaConnect -
Quam Erogbogbo
San Francisco Bay AreaConnect -
Alex Carroll
Greater Seattle AreaConnect -
Tarek Mustapha
Artist, Co-Founder and CTO at Fewture Co.
Glendora, CAConnect -
Scott Turner
Proven Executive Leader with 40+ years experience in B2B sales, operations and P&L Management.
Green Bay, WIConnect -
Sibylle Mair
Vice President of Finance and Controlling at Hansgrohe
Suwanee, GAConnect -
Hagos mesgoun
--
United StatesConnect -
Keith Bigelow
CanadaConnect -
Andrew Dillard
Redondo Beach, CAConnect -
Brian Sparling
San Francisco Bay AreaConnect -
David Bingham
Boulder, COConnect -
Nihar Vaidya
San Ramon, CAConnect -
Srdjan Kovacevic, PhD
Palo Alto, CAConnect -
Todd Porter
Saint Johns, FLConnect
Explore more posts
-
Scott Griffiths
The Information has a great write-up about the intense battle for foundational data storage companies namely Snowflake and Databricks and who really has the pole position. It is a great read for a part of the technology stack that frequently does not get the headlines they deserve. What do you think? #mangement #venturecapital #privateequity #cloudcomputing #capitalmarkets
1 -
Anupam Rastogi
All of these statements about enterprise AI could simultaneously be true, even if they seem somewhat contradictory: 🌟 Hype will come and go, but GenAI will be a game changer for automating mundane parts of numerous enterprise workflows 🏗️ Making GenAI work within core workflows in the enterprise takes tremendous hard work beyond getting the tech to work - meticulous data pipelines, ensuring accuracy across real-life scenarios, safeguards against hallucination, robust guardrails, on-prem deployment capabilities where needed, change management and more, all while ensuring predictable and acceptable costs. Once done successfully, all this effort creates moats ⚙️ Large models may work out-of-the-box for some basic horizontal business tasks. Applications built around domain-specific models will work much better for many other tasks. Agentic workflows are one likely path to broader automation 👥🤖 Human Augmentation and Human-in-the-loop automation is what is here-and-now. Full automation solutions - outside of simple, low consequence tasks - will take time to perfect and be sufficiently trusted in the enterprise 🚫🎯 Enterprises will not buy “GenAI”. They will buy solutions and outcomes. If a GenAI-powered solution is the optimal one for their needs, then that will be bought 🔄 GenAI has opened tremendous opportunities for enterprise software startups that do other adjacent things to make their products more relevant, usable or actionable, and ‘close the loop’ ⚠️ Many “GenAI for X” startups will fail to deliver value in the enterprise. Many GenAI-native startups with the right solution and approach will be massive home runs. Success comes from focusing on the entire solution you are delivering, not just the technology that enabled it 🛠️ Some Enterprise AI startups will need to become services companies in order to deliver value 🕶️ Some Enterprise AI startups will succeed without becoming services companies 🤹 Both open source and proprietary foundation models will be used in enterprise AI deployments - several models may get used within the same application. The best model will win - on a per API call basis For many things being talked about enterprise AI, the claim and counterclaim could both be simultaneously true. Augmentation and automation of enterprise workflows is a massive undertaking that is broad, wide, deep and extremely bespoke. AI-fication of work and workflows is one of the biggest opportunities in our lifetimes. Things are just getting started!
4610 Comments -
Ilya Lysov
1/ Uncomfortable $10B question for $DELL 😳 Analyst Toni Sacconaghi asked a simple yet brutal Q: Why didn't operating profit change when $DELL added $1.7B worth of servers for #AI services? #earnings #tech 2/ The implication? $DELL's operating margin on #AI servers is effectively zero! 😲 A single Q led to a $10B drop in market cap. Ouch! #investors #stockmarket 3/ Are chipmakers the real #winners of the #AI hype? 🤔 While tech giants chase AI, semiconductor companies rake in profits from high demand. #analytics #bigdata 4/ $DELL's situation reminds us that not everyone benefits equally from new tech trends. 📉 The road to #AI domination is paved with costly investments. #riskvreward #innovation 5/ A $10B question indeed! 💸 One analyst's query exposed potential cracks in $DELL's #AI strategy. Will they course-correct or get left behind? 🔭 #disruptor #futuretech 6/ In the world of finance, simple Qs can have massive impacts. 💥 $DELL's case shows why public companies must be transparent & prepared. #accountability #shareholdervalue 7/ The AI wave is rising, but who'll be the real surf champions? 🌊 Tech titans or component suppliers? An exciting race to watch! #competition #disruption 8/ Perhaps $DELL's AI conundrum serves as a wake-up call. 💡 Pivoting to new tech requires careful planning & execution. No room for rookie mistakes! #strategy #leadership 9/ While some rejoice at $DELL's $10B stumble, others see an opportunity. 👀 A shake-up could spur innovation & realign priorities. #transformation #pivot 10/ In the end, the $10B Q highlights the complexities of the #AI revolution. 🧩 Not every player will emerge a winner, but the game's just begun! #futureisnow #techbuzz
21 Comment -
Saket Saurabh
So what’s common between: 1. Blitzscaling a Consumer business 2. Running hyper-targeted advertising at scale 3. Building cutting edge production-grade GenAI The answer is fast, scalable, and reliable, enterprise grade Data Integrations across a very diverse set of systems. Every business wants to be data-driven, but bringing ready-to-use data at its point of use is not easy. It takes amazing engineering along with powerful platforms, such as Nexla. Don’t miss our Data Leaders panel tomorrow with - Nikita Tovstoles - Director of Engineering, formerly at DoorDash - Abhishek Jain - Platform Architect at LiveRamp - Darrel Cherry - Distinguished Engineer at Clearwater Analytics Each speaker will discuss their work on challenging data integration cases, detailing how they approached delivering data from diverse sources and formats to meet various system and business requirements at speed and scale. Register here: https://lnkd.in/gWdArPxg Date: Tuesday, April 16, 2024 Time: 11:00 AM PT / 2:00 PM ET #DataIntegration #Webinar #DataLeadership #GenAI #DataAnalytics #Datascience #Dataproducts #Dataengineering
16 -
Cris Ippolite
🚨EPISODE 10 ALERT : #Claris TALK #AI Podcast 🚨 In this VIDEO 🎥 episode, Matt and Cris talk about whether Language Models are Databases Cris and Matt dive into a discussion about the fundamental differences between databases and large language models (LLMs). We discuss how developers should be responsible for supplying truth and context to AI models through "retrieval augmented generation" (RAG) rather than relying on the model's inherent knowledge. An example is given of assessing ChatGPT's latent knowledge of FileMaker, which scored around 64% accuracy, highlighting the need for the Claris community to contribute to a shared knowledge base to improve the model. The episode also covers recent announcements in the AI space, including Google's Gemini LLMs with expanded token windows, OpenAI's GPT-4 with multimodal capabilities and enhanced conversational features, and Microsoft's Copilot integrations. The hosts speculate about Apple's upcoming AI play at #WWDC24, predicting improvements to Siri, on-device AI and Copilot-like assistants in their platforms. Cris shares a book recommendation, "Brave New Worlds" by Sal Khan, and discusses the potential for AI to serve as a personalized learning companion. The hosts also touch on upcoming FileMaker conferences.
3 -
Adam Devine
Just wrapped a webinar with PEI about data unification alongside Pete Keenan. It's a good thing he knows what he's talking about - I mostly just smiled and nodded and said "totally" every once in a while after he talked. It's clear from a survey we fielded during the webinar that even the biggest venture and private equity managers haven't solved the golden record problem. As more data piles into the private market alongside more demanding institutional LPs, the problem is only going to get bigger, and you can't just slap an LLM on it. Comment or DM if you're in VC or PE finance and want to learn more - I know some smart people for you to talk to.
213 Comments -
Tarush Aggarwal
This is something we have been looking forward to for a while. 🏇 We started 5X with the mission to make data simple. Data is one of the most fragmented industries, with over 500 vendors in 10+ categories. The analogy we use is that data vendors are selling car parts. Imagine walking into a Honda dealership, and instead of selling you a Civic, they sold you an engine, and you had to build your own car. For 90% of companies buying cat parts makes absolutely no sense. 🤯 They want a complete platform (car) that works out of the box. 🚀 We're very excited to announce the launch of 5X BI. 🚀 With the launch of 5X BI, we now offer a complete data platform – ingestion, warehousing, modeling, and business intelligence – all in one place. Whether you're a data engineer, data analyst, data scientist, PM, stakeholder or executive, 5X has got you covered. Learn more about 5X BI and how it's transforming businesses Here -> https://lnkd.in/gdEAB9H6
426 Comments -
Matt Turck
Databricks acquiring Tabular (for $1B) and OpenAI acquiring Rockset (for 9 figures in stock) both point to consolidation and an exit path for data/AI startups, including those that built a great product but never hit meaningful commercial traction. Just one problem - Potential acquirers: OpenAI, Anthropic, Databricks, Snowflake, maybe Microsoft, couple others Startups that would like to be acquired:👇👇👇
1,53896 Comments -
Ed Brandman
You don’t need to be a prompt engineer to leverage prompt engineering. It is important to realize that how you “talk” to LLMs still matters a lot. I think even with the rapid advancements we are seeing, this skill will remain critical for some time to come given the wide body of research and direct experience that confirms how impactful it can be in a conversation with GenAI. This is a great use of Claude, try it out.
53 Comments -
Dakshin - Blooomit Capital
Unveiling the powerhouse behind data management! Ever heard of a $43 Billion juggernaut that's not just storing data but revolutionizing how it's utilized? Enter Databricks—a behemoth managing data for over 9,000 colossal companies. Brace yourselves for some eye-opening stats: With a whopping $3.5 Billion raised from 7 funding rounds, Databricks is not just another tech player—it's a game-changer in the data realm. Now, let's dissect the secrets to their meteoric rise: 1) Pioneering commercial data management: In 2013, when data management solutions were scarce, Databricks stepped in to fill the void. By offering the first commercial platform for handling vast datasets, they established themselves as trailblazers in the field. 2) Raising the bar on code quality: While existing platforms like Spark laid the groundwork, Databricks took it up a notch. By creating a proprietary platform, they ensured consistent code quality, setting themselves apart in a sea of open-source alternatives. 3) All-in-one functionality: Databricks isn't just a platform—it's a comprehensive solution for data visualization, management, and analysis. With cost-effective, scalable features and built-in AI capabilities, they've redefined the data management landscape. So, what's the key to emulating Databricks's success? Identify untapped opportunities, seize the moment, and craft a solution that addresses industry gaps. By leveraging strategic connections and innovation, you too can carve out a niche and ascend to industry dominance. #Databricks #DataManagement #TechInnovation #StartupSuccess
2 -
Roman Stanek
GoodData's vision for the next-gen Analytics Infrastructure fundamentally differs from traditional #BI and #visualization tools. While building monolithic and closed architectures worked well for Tableau, PowerBI, and Qlik, today's VUCA (Volatility, Uncertainty, Complexity, Ambiguity) environment requires a very different, more agile, composable, and open approach with minimal vendor lock-in and an accelerated rate of innovation. Adding fast-evolving #GenAI technologies to the GoodData Cloud is a good example. What worked six months ago is now replaced by new #LLMs, more sophisticated vector databases, and #RAG (Retrieval-Augmented Generation) techniques for enhancing the accuracy and reliability of generative #AI models:
12 -
Niken Patel
Enterprises did not build their own CX, ERP applications. They ultimately run on best of breed Cloud applications, or are in the process of landing up there. There is no reason to believe that AI applications and use cases are going to be any different. Consider the cost of AI hiring (hiring NLP engineers away from Google or Meta?), the number of skill sets needed to build these solutions in-house, the probability of hitting the accuracy needed, etc. Customer are building in-house teams so that they can build AI into their own products (core to their business). And buying for operational efficiency across the other business units.
212 Comments -
Baris Aksoy
👀 Snowflake (data warehouse king) & Databricks (open source champion of data lake) are locked in a silent arms race to dominate the enterprise data/AI landscape. They both made strategic acquisitions to become THE enterprise cloud data/AI platform: ❄️ Snowflake acquired Appian Corporation (for unstructured data processing), LeapYear (acquired by Snowflake) (for data clean rooms/privacy), Neeva (for generative AI), and Streamlit (for data applications) to support its data analytics and AI offerings 🧱 Databricks acquired Arcion Labs (Acquired by Databricks) (for data ingestion), Databricks Mosaic Research (for generative AI), Okera (for AI governance), and Lilac AI (joined Databricks) (for unstructured data processing) to strengthen its data science and AI platform 🔮 What's next? This is just the beginning. I expect both to: 💥 Acquire specialized AI startups to fill niche gaps i.e. AI explainability/bias detection, MLOps, vertical-specific proprietary models, OS-based data solutions, etc. 💥 Blur the lines between open vs. closed platforms - Snowflake might tap more into OSS waters, Databricks might offer premium features. 💥Focus on developer experience - who builds the most developer-friendly platform for AI workflows? I'm betting on Databricks as open source & engineering-heavy culture give them an edge over Snowflake. But will those be enough against Snowflake's strong enterprise GTM muscle? 🤷🏻♂️ #datawarehouse #datalakes #llm #ml #ai #largelanguagemodels #analytics #cloud #data #opensource #oss #databricks #snowflake #generativeai #genai #gpt
311 Comment -
Varun Grover
🏅 Large Language Model Leaderboard 🏆 When it comes to evaluating different Large Language Models (LLMs) for your use case, understanding their relative strengths is key. 🏋♂️ Here's a concise breakdown: 1️⃣ Multitasking Understanding: Claude 3 Opus from Anthropic and GPT-4 from OpenAI lead in the MMLU benchmark for general knowledge. This makes them strong candidates for projects requiring a wide-ranging understanding. 2️⃣ Arithmetic Reasoning: In arithmetic, Claude 3 Opus scores highest, ideal for tasks that involve math or logical problem-solving. 3️⃣ Coding Proficiency: For coding tasks, Claude 3 Opus and Meta Llama 3 70B show top performance, perfect for software development support. 4️⃣ Context Window: Google's Gemini 1.5 Pro offers the largest context window, able to process extensive data at once, beneficial for complex tasks involving large volumes of text. 5️⃣ Cost-Efficiency: Meta Llama 3 8B stands out for its low input cost per token, offering a budget-friendly option without compromising too much on capability. Choosing the right LLM involves balancing these attributes against your specific requirements. Subscribe to Generative AI with Varun for more insights on LLMs: https://lnkd.in/dNZ4b7ix #GenerativeAI #LLM #OpenAI #Anthropic #Google #Meta
233 Comments -
Zaki E.
Evaluating LLM products isn't about just eyeballing and hoping for the best on a PowerPoint slide and a fancy product name ... You need a measurement plan that you can quantify success and performance... So how do we know if they're truly delivering? The answer lies in a combination of metrics that assess both the retrieval pipeline and the LLM response itself Pipeline Metrics 🛠️: - Precision: Accuracy in information retrieval 🔍. - Recall: Completeness of retrieved information ✔️. - F1 Score: Balances precision and recall ⚖️. - Latency: System's response speed ⏱️. - Efficiency: Throughput: System's query-handling capacity 📚. LLM Response Metrics 📝: - General Model Performance(i.e. Perplexity): Lower is better 👇. - Content Quality & Relevance: BLEU/ROUGE/METEOR Scores 🎯. - Meaning Preservation: Fidelity/Faithfulness ❤️. - Diversity Metrics: Entropy metrics 🔄. - Entity Preservation: Measures the overlap of named entities between generated and reference text 👥. - Completion Quality: Relevance/coherence of text 👌. Remember, Holistic evaluation of AI product is essential. Pick metrics based on your product goals/objectives. Combine automated metrics and human evaluation. Make informed decisions; don't leave it to guesswork ❌🎲. #dataproduct #productdesign #data #ai #llm
91 Comment -
Martin Mahler 📊☁️
Data story telling is the most powerful way to communicate information - a gallery of infographics 🖼 created by Stephanie French exclusively in Astrato Analytics, shows not only the flexibility of the pixel-perfect BI platform, but how easy it is to create a data-driven narrative. 📊 Try out Astrato for yourselves.
823 Comments -
Erkeda DeRouen, MD ✨ Digital Health Risk Management Consultant ⚕️TEDxer
TED Conferences are my jam! I watch them all the time. Here are some great ones that dive into AI. I look forward to catching them all ✨ P.s. I’ll shamelessly plug mine in the comments that talked about how we can innovate in healthcare by reimagining collaboration. It’s called “Did Disney Just Save Healthcare?!? Imagine This…” I think one of my future post will dive into some more healthcare innovation related ones. Does anyone have any suggestions? #ai #tedx #tedtalk #collaboration #innovation
11 Comment -
Sam Lee
Part II of our blog is out! In this installment Abde Tambawala and I explored usage metrics and pricing models across different AI modalities and discussed how traditional User-based subscriptions will need to be supplemented with usage metrics. Take a look and let us know what you think! #pricingstrategy #ai #monetization
272 Comments
Explore collaborative articles
We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.
Explore MoreOthers named Yonatan Hagos
-
Yonatan Hagos
Mechanical Engineer
Addis Ababa, Ethiopia -
Yonatan Hagos
Mechanical Engineer at Somali regional water development bureau
Jijiga -
Yonatan H. Hagos
Managing Partner at Sneakers & Bowties, LLC
Los Angeles, CA -
Yonatan Hagos
Student at Georgia Gwinnett College
Atlanta Metropolitan Area
12 others named Yonatan Hagos are on LinkedIn
See others named Yonatan Hagos