Nisan Haramati
@nisanharamati.bsky.social
Data Systems for Infinite Scale, Math, Physics, Croissants. Founder.
Reposted by Nisan Haramati
"How I, a non-developer, read the tutorial you, a developer, wrote for me, a beginner" by Annie Mueller 😅 😂 😭
anniemueller.com/posts/how-i-...
anniemueller.com/posts/how-i-...
How I, a non-developer, read the tutorial you, a developer, wrote for me, a beginner - annie's blog
“Hello! I am a developer. Here is my relevant experience: I code in Hoobijag and sometimes jabbernocks and of course ABCDE++++ (but never ABCDE+/^+ are you kidding? ha!) and I like working with ...
anniemueller.com
September 23, 2025 at 7:57 AM
"How I, a non-developer, read the tutorial you, a developer, wrote for me, a beginner" by Annie Mueller 😅 😂 😭
anniemueller.com/posts/how-i-...
anniemueller.com/posts/how-i-...
Reposted by Nisan Haramati
For the first time: @honeycomb.io is hiring open roles in Australia!!! We have this senior role open as well as a mid-level role. job-boards.greenhouse.io/honeycomb/jo...
Once we fill these, we will have a thriving APAC team of 5 people: Field CTO, account exec, customer architect, and 2 support.
Once we fill these, we will have a thriving APAC team of 5 people: Field CTO, account exec, customer architect, and 2 support.
Senior Technical Support Engineer- AUS
Remote - Australia
job-boards.greenhouse.io
September 18, 2025 at 3:53 AM
For the first time: @honeycomb.io is hiring open roles in Australia!!! We have this senior role open as well as a mid-level role. job-boards.greenhouse.io/honeycomb/jo...
Once we fill these, we will have a thriving APAC team of 5 people: Field CTO, account exec, customer architect, and 2 support.
Once we fill these, we will have a thriving APAC team of 5 people: Field CTO, account exec, customer architect, and 2 support.
Reposted by Nisan Haramati
The legacy observability vendors' obsession with "cardinality control" is so backwards.
Why *control* cardinality instead of *embracing* it? High-cardinality data isn't a bug—it's the entire point. Your complex systems generate complex data.
Stop building tools that fight reality.
Why *control* cardinality instead of *embracing* it? High-cardinality data isn't a bug—it's the entire point. Your complex systems generate complex data.
Stop building tools that fight reality.
September 3, 2025 at 7:23 PM
The legacy observability vendors' obsession with "cardinality control" is so backwards.
Why *control* cardinality instead of *embracing* it? High-cardinality data isn't a bug—it's the entire point. Your complex systems generate complex data.
Stop building tools that fight reality.
Why *control* cardinality instead of *embracing* it? High-cardinality data isn't a bug—it's the entire point. Your complex systems generate complex data.
Stop building tools that fight reality.
Reposted by Nisan Haramati
#SemanticSearch #DataInfrastructure #SearchArchitecture
Our latest post, www.graphiumlabs.com/blog/end-of-..., discusses how current search systems and tools are falling apart as they are required to handle an ever growing mass of data, and an increasing level of nuance and complexity.
Our latest post, www.graphiumlabs.com/blog/end-of-..., discusses how current search systems and tools are falling apart as they are required to handle an ever growing mass of data, and an increasing level of nuance and complexity.
The End of Lookup - Rethinking Search as Infrastructure — Graphium Labs-
Traditional keyword search is failing. A new, context-aware, intent-based search is emerging as essential infrastructure for better decision-making.
www.graphiumlabs.com
September 2, 2025 at 5:30 PM
#SemanticSearch #DataInfrastructure #SearchArchitecture
Our latest post, www.graphiumlabs.com/blog/end-of-..., discusses how current search systems and tools are falling apart as they are required to handle an ever growing mass of data, and an increasing level of nuance and complexity.
Our latest post, www.graphiumlabs.com/blog/end-of-..., discusses how current search systems and tools are falling apart as they are required to handle an ever growing mass of data, and an increasing level of nuance and complexity.
Reposted by Nisan Haramati
I think they might be coming back. Have you seen www.graphiumlabs.com?
Search You Can Trust - Graphium Labs Semantic Search
Today's search tools do approximate searches or hallucinate answers. We don't. Our semantic search handles a trillion queries per month, with 100% recall & precision, finding everything that matters, ...
www.graphiumlabs.com
June 6, 2025 at 2:16 AM
I think they might be coming back. Have you seen www.graphiumlabs.com?
Reposted by Nisan Haramati
This post breaks down why understanding precision and recall is essential when building search and information retrieval systems for high stakes decision making:
www.graphiumlabs.com/blog/precisi...
www.graphiumlabs.com/blog/precisi...
100% Recall and 100% Precision in Modern Search — Graphium Labs-
Precision and recall aren’t just technical jargon—they make up the difference between trust and risk in modern search systems. And they matter more than most people think.
www.graphiumlabs.com
July 24, 2025 at 6:44 PM
This post breaks down why understanding precision and recall is essential when building search and information retrieval systems for high stakes decision making:
www.graphiumlabs.com/blog/precisi...
www.graphiumlabs.com/blog/precisi...
Reposted by Nisan Haramati
In high-stakes environments, like medical diagnostics, legal research, and threat detection, the trade off between high recall and high precision isn’t just a theoretical optimization problem. The choice has real-world consequences.
July 24, 2025 at 6:44 PM
In high-stakes environments, like medical diagnostics, legal research, and threat detection, the trade off between high recall and high precision isn’t just a theoretical optimization problem. The choice has real-world consequences.
Reposted by Nisan Haramati
Ideally, users want both at 100% – all (good) signal, and zero noise. But the way search works under the hood often forces a trade off: higher recall requires looser filters to bring in more results, and consequentially, more irrelevant results or noise, which bring down precision.
July 24, 2025 at 6:44 PM
Ideally, users want both at 100% – all (good) signal, and zero noise. But the way search works under the hood often forces a trade off: higher recall requires looser filters to bring in more results, and consequentially, more irrelevant results or noise, which bring down precision.
Reposted by Nisan Haramati
Precision means: “Of the results that were returned, how many were relevant (correct)?”
And recall says: “Of all the correct results, how many were returned?”
And recall says: “Of all the correct results, how many were returned?”
July 24, 2025 at 6:44 PM
Precision means: “Of the results that were returned, how many were relevant (correct)?”
And recall says: “Of all the correct results, how many were returned?”
And recall says: “Of all the correct results, how many were returned?”
Reposted by Nisan Haramati
In search and information retrieval systems, precision and recall are more than just evaluation metrics—they reflect how well a system aligns with the user’s needs and expectations of relevance and completeness.
July 24, 2025 at 6:44 PM
In search and information retrieval systems, precision and recall are more than just evaluation metrics—they reflect how well a system aligns with the user’s needs and expectations of relevance and completeness.
Reposted by Nisan Haramati
New Graphium Labs blog post!
www.graphiumlabs.com/blog/precisi...
#precision #recall #relevance #search #informationretrieval #searchengineering #searchsystems #searchquality #mlmetrics
www.graphiumlabs.com/blog/precisi...
#precision #recall #relevance #search #informationretrieval #searchengineering #searchsystems #searchquality #mlmetrics
100% Recall and 100% Precision in Modern Search — Graphium Labs-
Precision and recall aren’t just technical jargon—they make up the difference between trust and risk in modern search systems. And they matter more than most people think.
www.graphiumlabs.com
July 24, 2025 at 6:44 PM
It's been bothering me for years how "Semantic" in "Semantic search", the way it's built these days, is semantically wrong.
So on this quite lovely Canada day, let's argue semantics about "Semantic".
So on this quite lovely Canada day, let's argue semantics about "Semantic".
July 1, 2025 at 6:37 PM
It's been bothering me for years how "Semantic" in "Semantic search", the way it's built these days, is semantically wrong.
So on this quite lovely Canada day, let's argue semantics about "Semantic".
So on this quite lovely Canada day, let's argue semantics about "Semantic".
Super excited to share this! I've known Saem for many years, and once we started talking about what we're building at Graphium Labs, having him join us as CEO felt inevitable.
Big news: Saem Ghani (@saemg.bsky.social) is joining Graphium Labs as CEO!
He’s led SaaS + large-scale data systems for enterprise—now he’s driving our next chapter.
Come meet him & the team at Web Summit Vancouver, May 27–30. We’ll be at the booth!
He’s led SaaS + large-scale data systems for enterprise—now he’s driving our next chapter.
Come meet him & the team at Web Summit Vancouver, May 27–30. We’ll be at the booth!
April 17, 2025 at 4:11 PM
Super excited to share this! I've known Saem for many years, and once we started talking about what we're building at Graphium Labs, having him join us as CEO felt inevitable.
Reposted by Nisan Haramati
I found the most incredible graph on the other site
April 13, 2025 at 5:50 PM
I found the most incredible graph on the other site
This was a really fun talk to give. Thanks Kir Shatrov and Cameron Morgan for organizing, and @tavis.damnsimple.com for recording!
Video: m.youtube.com/watch?v=D4ZL...
Slides: www.graphiumlabs.com/vancouver-sy...
Video: m.youtube.com/watch?v=D4ZL...
Slides: www.graphiumlabs.com/vancouver-sy...
April 9, 2025 at 4:28 PM
This was a really fun talk to give. Thanks Kir Shatrov and Cameron Morgan for organizing, and @tavis.damnsimple.com for recording!
Video: m.youtube.com/watch?v=D4ZL...
Slides: www.graphiumlabs.com/vancouver-sy...
Video: m.youtube.com/watch?v=D4ZL...
Slides: www.graphiumlabs.com/vancouver-sy...
I love this paper!
In the last week I probably explained Rateless Set Reconciliation to a dozen other scientists. What an amazing paper and result, and already one year old.
April 7, 2025 at 7:13 PM
I love this paper!
Reposted by Nisan Haramati
New Change, Technically episode is out: WHO'S AFRAID OF MATH?
We tackle *math anxiety," @analog-ashley.bsky.social teaches me about vulnerable circuits in the brain and being vulnerable about teaching, and I read a HECK of a lot of science to bring you this episode
We tackle *math anxiety," @analog-ashley.bsky.social teaches me about vulnerable circuits in the brain and being vulnerable about teaching, and I read a HECK of a lot of science to bring you this episode
March 28, 2025 at 5:58 PM
New Change, Technically episode is out: WHO'S AFRAID OF MATH?
We tackle *math anxiety," @analog-ashley.bsky.social teaches me about vulnerable circuits in the brain and being vulnerable about teaching, and I read a HECK of a lot of science to bring you this episode
We tackle *math anxiety," @analog-ashley.bsky.social teaches me about vulnerable circuits in the brain and being vulnerable about teaching, and I read a HECK of a lot of science to bring you this episode
Why "geometric" is bad:
Geometric refers to a geometric sequence in math, of the form a, ar, ar^2, ar^3, ..., ar^n.
If r>1 and the scale of something grows by the power, you lose control FAST. Nuclear meltdown fast. 99.9999% of the increase occurs in the last microsecond.
Fine -> BAD happens fast
Geometric refers to a geometric sequence in math, of the form a, ar, ar^2, ar^3, ..., ar^n.
If r>1 and the scale of something grows by the power, you lose control FAST. Nuclear meltdown fast. 99.9999% of the increase occurs in the last microsecond.
Fine -> BAD happens fast
It's easy to hear what @jay.bsky.team says about outages and the response and think "well that doesn't seem that hard to me?"
It's not, in your small-scale environments. Scale introduces geometric levels of complexity / problem.
It's not, in your small-scale environments. Scale introduces geometric levels of complexity / problem.
March 28, 2025 at 1:23 PM
Why "geometric" is bad:
Geometric refers to a geometric sequence in math, of the form a, ar, ar^2, ar^3, ..., ar^n.
If r>1 and the scale of something grows by the power, you lose control FAST. Nuclear meltdown fast. 99.9999% of the increase occurs in the last microsecond.
Fine -> BAD happens fast
Geometric refers to a geometric sequence in math, of the form a, ar, ar^2, ar^3, ..., ar^n.
If r>1 and the scale of something grows by the power, you lose control FAST. Nuclear meltdown fast. 99.9999% of the increase occurs in the last microsecond.
Fine -> BAD happens fast
This was a really fun talk to write and present!
Co-founder @nisanharamati.bsky.social gave a talk at last night's Vancouver.systems , "The Limits of Scaling and the Physical Properties of Data" going over how to predict the size limit where distributed systems stop scaling and start losing throughput.
slides: www.graphiumlabs.com/vancouver-sy...
slides: www.graphiumlabs.com/vancouver-sy...
March 11, 2025 at 8:23 PM
This was a really fun talk to write and present!
Reposted by Nisan Haramati
Co-founder @nisanharamati.bsky.social gave a talk at last night's Vancouver.systems , "The Limits of Scaling and the Physical Properties of Data" going over how to predict the size limit where distributed systems stop scaling and start losing throughput.
slides: www.graphiumlabs.com/vancouver-sy...
slides: www.graphiumlabs.com/vancouver-sy...
March 11, 2025 at 8:23 PM
Co-founder @nisanharamati.bsky.social gave a talk at last night's Vancouver.systems , "The Limits of Scaling and the Physical Properties of Data" going over how to predict the size limit where distributed systems stop scaling and start losing throughput.
slides: www.graphiumlabs.com/vancouver-sy...
slides: www.graphiumlabs.com/vancouver-sy...
Reposted by Nisan Haramati
We don't talk enough about Scaling to Catastrophe in distributed systems. Today's post, part 2 in the Physical Properties of Data series, explores the different scaling phases through the lens and math of the Universal Scalability Law. www.graphiumlabs.com/blog/part2-g... #databs #dataengineering
Part 2: Working with Gunther's Universal Scalability Law — Hypergraph by Graphium Labs-
This post will help you understand where you are on the scaling life cycle and therefore how close or far you are at any given time to a critical failure point.
www.graphiumlabs.com
February 25, 2025 at 8:04 PM
We don't talk enough about Scaling to Catastrophe in distributed systems. Today's post, part 2 in the Physical Properties of Data series, explores the different scaling phases through the lens and math of the Universal Scalability Law. www.graphiumlabs.com/blog/part2-g... #databs #dataengineering
Reposted by Nisan Haramati
bc i haven't done so yet, i decided to burn any remaining bridge to the land of statistics. it wasn't statisticians nor statistics but it was me. i am simply not good enough to do statistics myself.
so, @peyrardmax.bsky.social and i decided to turn statistical estimation into supervised learning.
so, @peyrardmax.bsky.social and i decided to turn statistical estimation into supervised learning.
February 18, 2025 at 6:12 PM
bc i haven't done so yet, i decided to burn any remaining bridge to the land of statistics. it wasn't statisticians nor statistics but it was me. i am simply not good enough to do statistics myself.
so, @peyrardmax.bsky.social and i decided to turn statistical estimation into supervised learning.
so, @peyrardmax.bsky.social and i decided to turn statistical estimation into supervised learning.
Reposted by Nisan Haramati
Hey #PlatformEngineering folks (especially with Kafka experience!) - how would you like to be the new Terra at @honeycomb.io? They are hiring a Staff Platform Engineer to backfill for me (my last day is Friday) and you couldn’t ask for a better group of folks.
jobs.lever.co/honeycomb/4f...
jobs.lever.co/honeycomb/4f...
Honeycomb - Staff Platform Engineer
What We’re Building Honeycomb is the observability platform for teams who manage software that matters. Send any data to our one-of-a-kind data store, solve problems with all the relevant context, and...
jobs.lever.co
December 11, 2024 at 3:02 AM
Hey #PlatformEngineering folks (especially with Kafka experience!) - how would you like to be the new Terra at @honeycomb.io? They are hiring a Staff Platform Engineer to backfill for me (my last day is Friday) and you couldn’t ask for a better group of folks.
jobs.lever.co/honeycomb/4f...
jobs.lever.co/honeycomb/4f...
Reposted by Nisan Haramati
There's a few tickets left for the distributed systems class coming up in just over a week. If you'd like to join, now's the time. :-)
https://www.eventbrite.com/e/distributed-systems-fundamentals-registration-1060426286569?aff=mastodon
https://www.eventbrite.com/e/distributed-systems-fundamentals-registration-1060426286569?aff=mastodon
Distributed Systems Fundamentals
Learn the theory and practice behind distributed systems, from safety and liveness to deployment and monitoring.
www.eventbrite.com
December 4, 2024 at 6:30 PM
There's a few tickets left for the distributed systems class coming up in just over a week. If you'd like to join, now's the time. :-)
https://www.eventbrite.com/e/distributed-systems-fundamentals-registration-1060426286569?aff=mastodon
https://www.eventbrite.com/e/distributed-systems-fundamentals-registration-1060426286569?aff=mastodon
Reposted by Nisan Haramati
Similarity measurement is the key element in recommendation systems: which entities or objects in your dataset are similar to others, and by how much, is the engine that drives recommendation systems
Read more in our latest blog post at www.graphiumlabs.com/blog/similar...
#databs #dataengineering
Read more in our latest blog post at www.graphiumlabs.com/blog/similar...
#databs #dataengineering
www.graphiumlabs.com
November 22, 2024 at 9:20 PM
Similarity measurement is the key element in recommendation systems: which entities or objects in your dataset are similar to others, and by how much, is the engine that drives recommendation systems
Read more in our latest blog post at www.graphiumlabs.com/blog/similar...
#databs #dataengineering
Read more in our latest blog post at www.graphiumlabs.com/blog/similar...
#databs #dataengineering