https://ashvardanian.com/ Recent content on Ash's Blog https://ashvardanian.com/branding/og-card.jpg https://ashvardanian.com/branding/og-card.jpg Hugo en Fri, 20 Mar 2026 00:00:00 +0000 https://ashvardanian.com/posts/numkong/ Fri, 20 Mar 2026 00:00:00 +0000 https://ashvardanian.com/posts/numkong/ Around 2&#39;000 SIMD kernels for mixed-precision BLAS-like numerics — dot products, batched GEMMs, distances, geospatial, ColBERT MaxSim, and mesh alignment — from Float6 to Float118, leveraging RISC-V, Intel AMX, Arm SME, and WebAssembly Relaxed SIMD, in 7 languages and 5 MB. https://ashvardanian.com/posts/search-utf8/ Mon, 15 Dec 2025 00:00:00 +0000 https://ashvardanian.com/posts/search-utf8/ ICU gets Unicode right and pays for it. This post shows a different approach: fold-safe windows, SIMD probes, and verifiers for fast UTF‑8 search. https://ashvardanian.com/posts/chacha-vs-aes-2025/ Fri, 07 Nov 2025 00:00:00 +0000 https://ashvardanian.com/posts/chacha-vs-aes-2025/ AES-256-GCM now beats ChaCha20-Poly1305 by up to 3x on every modern CPU with hardware acceleration, reversing the 2015 mobile performance advice. https://ashvardanian.com/posts/scaling-elections/ Tue, 28 Oct 2025 00:00:00 +0000 https://ashvardanian.com/posts/scaling-elections/ Taking the computationally expensive Schulze voting method from theory to practice on GPUs — exploring parallel algorithms, hardware optimizations, and why Mojo surprised me. https://ashvardanian.com/posts/aws-graviton-checksums-on-neon-vs-sve/ Mon, 06 Oct 2025 00:00:00 +0000 https://ashvardanian.com/posts/aws-graviton-checksums-on-neon-vs-sve/ SVE2 AES on AWS Graviton 4 delivers 2x faster string hashing than NEON, but SVE&#39;s variable-length promise fell flat: Graviton 4 regressed to 128-bit vectors. https://ashvardanian.com/posts/llm-epicycles/ Thu, 02 Oct 2025 00:00:00 +0000 https://ashvardanian.com/posts/llm-epicycles/ Like Ptolemaic astronomers stacking circles to predict planetary motion, we stack transformer layers to approximate intelligence—accurate yet awaiting our Kepler moment. https://ashvardanian.com/posts/image-processing-with-strings/ Sat, 20 Sep 2025 00:00:00 +0000 https://ashvardanian.com/posts/image-processing-with-strings/ StringZilla&#39;s SIMD-optimized Look-Up Tables beat OpenCV by 4x on image processing, proving string manipulation techniques excel beyond text. https://ashvardanian.com/posts/stringwars-on-gpus/ Mon, 15 Sep 2025 00:00:00 +0000 https://ashvardanian.com/posts/stringwars-on-gpus/ StringZilla v4 brings CUDA acceleration for string processing: 109x faster than Nvidia&#39;s CuDF on edit distances, plus 52-bit MinHash fingerprinting and AES-based hashing. https://ashvardanian.com/posts/beyond-openmp-in-cpp-rust/ Tue, 20 May 2025 00:00:00 +0000 https://ashvardanian.com/posts/beyond-openmp-in-cpp-rust/ Most C++ and Rust thread pools run 10x slower than OpenMP on fork-join workloads. Fork Union closes the gap to 20% with 300 lines, dodging mutexes and CAS. https://ashvardanian.com/posts/less-wrong-cuda-hello-world/ Sat, 05 Apr 2025 00:00:00 +0000 https://ashvardanian.com/posts/less-wrong-cuda-hello-world/ Moving beyond triple-bracket kernel launches to production-ready CUDA: proper error handling, CUDA Driver API, cooperative groups, and inline PTX for robust GPU code. https://ashvardanian.com/posts/longest-ptx-instruction/ Wed, 05 Feb 2025 00:00:00 +0000 https://ashvardanian.com/posts/longest-ptx-instruction/ Exploring the 79-character mma.sp::ordered_metadata instruction for Tensor Cores on Hopper H100s, plus insights on PTX, SASS, and the evolving complexity of GPU ISAs. https://ashvardanian.com/posts/cpu-ports/ Sun, 19 Jan 2025 00:00:00 +0000 https://ashvardanian.com/posts/cpu-ports/ By exploiting CPU port differences between Intel and AMD, interleaving FMA with addition instructions boosts AVX-512 reduction kernels from 211 GB/s to 330 GB/s per core. https://ashvardanian.com/posts/parsing-json-with-allocators-cpp/ Tue, 07 Jan 2025 00:00:00 +0000 https://ashvardanian.com/posts/parsing-json-with-allocators-cpp/ Custom allocators can dramatically reduce JSON parsing overhead, but singleton dependencies lurk everywhere—from malloc to std::isspace—limiting multi-threaded gains. https://ashvardanian.com/posts/splitting-strings-cpp/ Thu, 02 Jan 2025 00:00:00 +0000 https://ashvardanian.com/posts/splitting-strings-cpp/ A 16-year-old StackOverflow question on string splitting gets a modern answer: SIMD-accelerated tokenization that&#39;s 10x faster than STL and cleaner than ranges. https://ashvardanian.com/posts/next-31-years-of-unum/ Tue, 26 Nov 2024 00:00:00 +0000 https://ashvardanian.com/posts/next-31-years-of-unum/ Nine years into a 40-year commitment to AI infrastructure. Reflecting on mistakes, open-source wins, and why the real work is just beginning. https://ashvardanian.com/posts/understanding-simd-complexity/ Mon, 25 Nov 2024 00:00:00 +0000 https://ashvardanian.com/posts/understanding-simd-complexity/ Why SIMD programming is harder than it looks: exploring cosine similarity optimization across x86 and Arm architectures, from basic AVX2 to cutting-edge SVE2 instructions. https://ashvardanian.com/posts/simd-set-intersections-sve2-avx512/ Mon, 16 Sep 2024 00:00:00 +0000 https://ashvardanian.com/posts/simd-set-intersections-sve2-avx512/ Achieving 5x faster set intersections on AWS Graviton 4 using Arm&#39;s SVE2 and Intel&#39;s AVX-512 with specialized instructions like HISTCNT, MATCH, and VP2INTERSECT. https://ashvardanian.com/posts/discount-on-keyword-arguments-in-python/ Sun, 08 Sep 2024 00:00:00 +0000 https://ashvardanian.com/posts/discount-on-keyword-arguments-in-python/ Keyword arguments in Python aren&#39;t free. Switching from PyArg_ParseTupleAndKeywords to METH_FASTCALL and manual parsing yields a 35% speedup in function calls. https://ashvardanian.com/posts/numpy-vs-blas-costs/ Tue, 12 Mar 2024 00:00:00 +0000 https://ashvardanian.com/posts/numpy-vs-blas-costs/ NumPy&#39;s binding overhead wastes up to 90% of BLAS throughput on dot products; SimSIMD recovers that performance with optimized Python interfaces. https://ashvardanian.com/posts/painful-strings/ Mon, 12 Feb 2024 00:00:00 +0000 https://ashvardanian.com/posts/painful-strings/ C++ STL strings bring 20,000+ lines of code to every compilation, yet remain slower than LibC and error-prone. StringZilla offers a faster, more intuitive alternative. https://ashvardanian.com/posts/usearch-molecules/ Mon, 20 Nov 2023 00:00:00 +0000 https://ashvardanian.com/posts/usearch-molecules/ Indexing 28 billion chemical embeddings from 7 billion molecules using optimized Jaccard distance kernels, achieving 99% recall at 3,700 QPS on AWS Open Data. https://ashvardanian.com/posts/porting-cpp-library-to-ten-languages/ Thu, 09 Nov 2023 00:00:00 +0000 https://ashvardanian.com/posts/porting-cpp-library-to-ten-languages/ Binding USearch to 10 languages reveals the friction in each ecosystem—from Python&#39;s simplicity to Java&#39;s complexity—and why C++ still rules performance-critical code. https://ashvardanian.com/posts/python-c-assembly-comparison/ Mon, 30 Oct 2023 00:00:00 +0000 https://ashvardanian.com/posts/python-c-assembly-comparison/ From pure Python to AVX-512 assembly, optimizing cosine similarity reveals a 2,500x speedup through SIMD, FP16, and VNNI instructions on modern Intel CPUs. https://ashvardanian.com/posts/gcc-12-vs-avx512fp16/ Mon, 23 Oct 2023 00:00:00 +0000 https://ashvardanian.com/posts/gcc-12-vs-avx512fp16/ Hand-written AVX-512FP16 SIMD code achieves 119x speedup over GCC&#39;s auto-vectorization for Jensen-Shannon divergence, using reciprocal square roots and FMA instructions. https://ashvardanian.com/posts/javascript-ai-vector-search/ Sat, 21 Oct 2023 00:00:00 +0000 https://ashvardanian.com/posts/javascript-ai-vector-search/ Supercharging JavaScript&#39;s TypedArray with C bindings and SIMD achieves 10x speedup over native Arrays for AI vector operations in Node.js. https://ashvardanian.com/posts/pybind11-cpython-tutorial/ Tue, 10 Oct 2023 00:00:00 +0000 https://ashvardanian.com/posts/pybind11-cpython-tutorial/ Switching from PyBind11 to direct CPython C API bindings reduced StringZilla&#39;s call latency by 5x, proving that understanding CPython internals pays dividends. https://ashvardanian.com/posts/simsimd-faster-scipy/ Sat, 07 Oct 2023 00:00:00 +0000 https://ashvardanian.com/posts/simsimd-faster-scipy/ AVX-512 and Arm SVE bring masked loads and native f16 math to vector distances. SimSIMD exploits both, running up to 200x faster than SciPy on modern CPUs. https://ashvardanian.com/posts/searching-stable-marriages/ Tue, 18 Jul 2023 00:00:00 +0000 https://ashvardanian.com/posts/searching-stable-marriages/ Replacing billion-entry preference lists with vector search indexes makes the Nobel Prize-winning Stable Marriage algorithm scale to real-world dating and database joins. https://ashvardanian.com/posts/stringzilla/ Mon, 10 Jul 2023 00:00:00 +0000 https://ashvardanian.com/posts/stringzilla/ StringZilla uses SIMD tricks to hit 16 GB/s substring search, beating standard libraries by 5-10x and parsing multi-terabyte files Python couldn&#39;t handle. https://ashvardanian.com/posts/abusing-vector-search/ Tue, 09 May 2023 00:00:00 +0000 https://ashvardanian.com/posts/abusing-vector-search/ Vector search isn&#39;t just for AI embeddings. Use HNSW for geo-spatial queries, stock covariance, chess positions, text tokens, and multi-modal recommendations with custom metrics. https://ashvardanian.com/posts/count-unique-strings/ Tue, 09 May 2023 00:00:00 +0000 https://ashvardanian.com/posts/count-unique-strings/ From junior to expert: four C++ solutions to count unique strings reveal 30x performance gaps. Proficiency dramatically impacts even trivial single-threaded code. https://ashvardanian.com/posts/my-sona/ Fri, 29 Apr 2022 00:00:00 +0000 https://ashvardanian.com/posts/my-sona/ A love story cut short — remembering Sona, who taught me what it means to truly care for others, build with purpose, and find someone who shares your frequency. https://ashvardanian.com/posts/google-benchmark/ Fri, 04 Mar 2022 00:00:00 +0000 https://ashvardanian.com/posts/google-benchmark/ Write faster C++ with Google Benchmark: measure everything from math micro-ops to sorting algorithms, and discover 60x speedups with simple compiler tricks. https://ashvardanian.com/posts/ddr4-bandwidth/ Sat, 29 Jan 2022 00:00:00 +0000 https://ashvardanian.com/posts/ddr4-bandwidth/ Why reaching DDR4&#39;s theoretical bandwidth is nearly impossible. CPU parallel reductions struggle to hit 60% saturation while GPU solutions easily exceed 79%. https://ashvardanian.com/posts/cuda-parallel-reductions/ Fri, 28 Jan 2022 00:00:00 +0000 https://ashvardanian.com/posts/cuda-parallel-reductions/ GPU code beats optimized CPU parallel reductions by 10x, reaching 879 GB/s. CUB achieves 94% bandwidth saturation while CPU barely hits 60%. https://ashvardanian.com/posts/apple-m1/ Tue, 21 Dec 2021 00:00:00 +0000 https://ashvardanian.com/posts/apple-m1/ M1 Max with DDR5 challenges 64-core server workloads in hash-table benchmarks. Memory bandwidth matters more than core count for many real-world tasks. https://ashvardanian.com/posts/server-supercycle/ Tue, 07 Dec 2021 00:00:00 +0000 https://ashvardanian.com/posts/server-supercycle/ DDR5, PCIe Gen5, CXL, and new CPUs from Intel, AMD, and NVIDIA converge in 2022. The biggest datacenter hardware refresh in a decade. https://ashvardanian.com/posts/simd-popularity/ Sun, 21 Nov 2021 00:00:00 +0000 https://ashvardanian.com/posts/simd-popularity/ Analysis of 2,000+ Linux and macOS binaries reveals less than 1% of instructions use SIMD, despite CPUs dedicating massive die area to vector processing. https://ashvardanian.com/posts/artsakh/ Fri, 02 Oct 2020 00:00:00 +0000 https://ashvardanian.com/posts/artsakh/ A data-driven argument for why Artsakh must be independent — examining historical claims, demographic evidence, and the indisputable pattern of ethnic violence. https://ashvardanian.com/posts/turkey/ Thu, 01 Oct 2020 00:00:00 +0000 https://ashvardanian.com/posts/turkey/ Seven stories tracing Turkey&#39;s path from secular reforms to neo-Ottoman ambitions — examining crimes unpunished, allies betrayed, and the dangerous pattern repeating today. https://ashvardanian.com/posts/aggressor/ Sun, 27 Sep 2020 00:00:00 +0000 https://ashvardanian.com/posts/aggressor/ Three countries, vastly different resources and freedoms. The numbers reveal who&#39;s really threatening peace in the region. https://ashvardanian.com/posts/armenia/ Sat, 01 Aug 2020 00:00:00 +0000 https://ashvardanian.com/posts/armenia/ Why Armenia is an emerging tech hub worth your attention — from startup tax incentives to ancient history, discover what makes this small nation punch above its weight. https://ashvardanian.com/posts/covid19/ Sun, 22 Mar 2020 00:00:00 +0000 https://ashvardanian.com/posts/covid19/ The pandemic revealed our weaknesses, but also unprecedented opportunities — from personal growth to financial markets, here&#39;s why optimism isn&#39;t naive. https://ashvardanian.com/posts/building-ai-safely/ Fri, 06 Jul 2018 00:00:00 +0000 https://ashvardanian.com/posts/building-ai-safely/ A 2018 conversation about AI safety, infrastructure, and the real dangers of weak AI in the hands of organizations optimizing for power over people. https://ashvardanian.com/posts/whats-wrong-with-wwdc-2016/ Tue, 14 Jun 2016 00:00:00 +0000 https://ashvardanian.com/posts/whats-wrong-with-wwdc-2016/ An iOS developer&#39;s critique of Apple&#39;s 2016 keynote — when emojis and animations overshadowed the innovations developers actually needed. https://ashvardanian.com/hackernews/ Mon, 01 Jan 0001 00:00:00 +0000 https://ashvardanian.com/hackernews/ <p>I often post on Reddit and HackerNews, with the latter being a surprisingly well-balanced platform for technical discussions with less personal bias. Here are some of my favorite publications that made headlines on HackerNews:</p> <ol> <li><a href="https://news.ycombinator.com/item?id=35042316">Up to 100x Faster FastAPI with simdjson and io_uring on Linux 5.19</a>.</li> <li><a href="https://news.ycombinator.com/item?id=34970045">Beating OpenAI CLIP with 100x less data and compute</a>.</li> <li><a href="https://news.ycombinator.com/item?id=43727743">Less Slow C++</a>.</li> <li><a href="https://news.ycombinator.com/item?id=46276826">Full Unicode Search at 50× ICU Speed with AVX‑512</a>.</li> <li><a href="https://news.ycombinator.com/item?id=45402820">Beyond OpenMP in C++ and Rust: Taskflow, Rayon, Fork Union</a></li> <li><a href="https://news.ycombinator.com/item?id=45304807">Processing Strings 109x Faster Than Nvidia on H100</a>.</li> <li><a href="https://news.ycombinator.com/item?id=42237938">Understanding SIMD: Infinite complexity of trivial problems</a></li> <li><a href="https://news.ycombinator.com/item?id=35887983">Abusing vector search for texts, maps, and chess</a>.</li> <li><a href="https://news.ycombinator.com/item?id=29670624">Apple to Apple Comparison: M1 Max vs. Intel</a>.</li> <li><a href="https://news.ycombinator.com/item?id=29954447">Server Hardware Super-Cycle 2022</a>.</li> <li><a href="https://news.ycombinator.com/item?id=30178764">Failing to reach DDR4 bandwidth</a>.</li> <li><a href="https://news.ycombinator.com/item?id=38684461">Python, C, Assembly – Faster Cosine Similarity</a>.</li> <li><a href="https://news.ycombinator.com/item?id=36772545">Combinatorial Stable Marriages for DBMS Semantic Joins</a>.</li> <li><a href="https://news.ycombinator.com/item?id=37273963">Faking SIMD to Search and Sort Strings 5x Faster</a>.</li> <li><a href="https://news.ycombinator.com/item?id=39111114">SimSIMD v3.6.7: Hardware-accelerated similarity metrics and distance functions</a>.</li> <li><a href="https://news.ycombinator.com/item?id=37304306">StringZilla v2: Fastest string sort, search, split, and shuffle using SIMD</a>.</li> </ol> https://ashvardanian.com/software/ Mon, 01 Jan 0001 00:00:00 +0000 https://ashvardanian.com/software/ <p>All of my software is hosted on GitHub, mostly under the <a href="https://opensource.org/licenses/Apache-2.0">Apache-2.0</a> permissive license. Free for commercial and non-commercial use, modification, and distribution.</p> <h2 id="major-projects">Major Projects</h2> <ul> <li><strong><a href="https://github.com/unum-cloud/USearch">USearch</a></strong> - one of the world&rsquo;s most popular search engines, used in databases, AI labs, and large-scale Natural Science experiments. Compact C++ core with 10+ language bindings — 10–100× faster than Meta FAISS for vector search and far beyond Apache Lucene.</li> <li><strong><a href="https://github.com/ashvardanian/StringZilla">StringZilla</a></strong> - one of the fastest string/text processing libraries, leveraging SIMD, SWAR, and CUDA-accelerated algorithms for search, matching, hashing, and sorting at Web-scale Unicode UTF-8 text and Petabyte-scale Bioinformatics data. Hundreds of hand-tuned kernels with manual multi-versioning, exposed to C, C++, Rust, Python, Swift, and JavaScript, up to 10× faster on CPUs and 100× faster on GPUs. <a href="https://github.com/ashvardanian/StringZilla-CLI">CLI</a> included.</li> <li><strong><a href="https://github.com/ashvardanian/NumKong">NumKong</a></strong> - one of the largest &amp; most-portable mixed-precision numerics projects for C, C++23, Python, Rust, and JavaScript. Designed for linear algebra, scientific computing, statistics, information retrieval, and image processing, delivering consistent SIMD speedups over BLAS and NumPy on x86, ARM, RISC-V, PowerPC, LoongArch, and in-browser WASM environments, bringing 6-, 8-, and 16-bit obscure GPU-only floats to every modern chip.</li> <li><strong><a href="https://github.com/ashvardanian/ForkUnion">ForkUnion</a></strong> - ultra-low-latency parallelism library for Rust and C++. Avoids allocations, mutexes, and even Compare-And-Swap atomics — achieving up to 10× speedups over Rayon and TaskFlow.</li> <li><strong><a href="https://github.com/unum-cloud/UCall">UCall</a></strong> - a kernel-bypass web server backend for C and Python built on io_uring. Achieves 70× higher throughput and 50× lower latency than FastAPI for real-time workloads, including serving compact AI models.</li> <li><strong><a href="https://github.com/unum-cloud/UForm">UForm</a></strong> - tiny multimodal AI models with state-of-the-art parameter and data efficiency. Compatible with Python, JS, and Swift, serving as a lightweight alternative to OpenAI CLIP for on-device and server inference.</li> </ul> <p>Some of those are used in open-source databases, like <a href="https://github.com/ClickHouse/ClickHouse">ClickHouse</a>, <a href="https://github.com/duckdb/duckdb">DuckDB</a>, <a href="https://github.com/pingcap/tidb">TiDB</a>, <a href="https://github.com/scylladb/scylladb">ScyllaDB</a>, <a href="https://github.com/yugabyte/yugabyte-db">yugabyteDB</a>, <a href="https://github.com/dragonflydb/dragonfly">DragonflyDB</a>, <a href="https://github.com/memgraph">MemGraph</a>, <a href="https://github.com/vdaas/vald">Vald</a>, <a href="https://github.com/tursodatabase/turso">Turso</a>, <a href="https://github.com/chroma-core/chroma">Chroma</a>, LLM toolchains, like <a href="https://github.com/langchain-ai/langchain">LangChain</a>, <a href="https://github.com/run-llama/semtools">LlamaIndex</a>, <a href="https://github.com/microsoft/semantic-kernel">Microsoft SemanticKernel</a>, <a href="https://github.com/nomic-ai/gpt4all">Nomic AI GPT4All</a>, <a href="https://github.com/deta/surf">Surf</a>, and many other less &ldquo;open&rdquo; systems, such as backend infrastructure of major AI labs, government intelligence agencies, hyperscale cloud companies, Fortune 500, iOS and Android apps with 100M-1B MAU.</p> https://ashvardanian.com/talks/ Mon, 01 Jan 0001 00:00:00 +0000 https://ashvardanian.com/talks/ <p>Most materials are in English unless <del>literally</del> flagged otherwise. The absolute majority is on the subjects of Systems Design, Computer Science, and Artificial Intelligence. The 🗣️ talking head links aren&rsquo;t technical, and in the ones with a 👯‍♂️ - I am just a wingman supporting another speaker.</p> <h2 id="2026">2026</h2> <div style="position: relative; padding-bottom: 56.25%; height: 0; overflow: hidden;"> <iframe allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share; fullscreen" loading="eager" referrerpolicy="strict-origin-when-cross-origin" src="https://www.youtube-nocookie.com/embed/sN4pZP98GUg?autoplay=0&amp;controls=1&amp;end=0&amp;loop=0&amp;mute=0&amp;start=0" style="position: absolute; top: 0; left: 0; width: 100%; height: 100%; border:0;" title="YouTube video"></iframe> </div> <ul> <li>PostNauka &ldquo;Think Like a Scientist&rdquo; Podcast #56: AI Infrastructure, Numeric Precision, and Search Systems. <a href="https://youtu.be/sN4pZP98GUg">YouTube</a>. 🇷🇺</li> </ul> <h2 id="2025">2025</h2> <div style="position: relative; padding-bottom: 56.25%; height: 0; overflow: hidden;"> <iframe allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share; fullscreen" loading="eager" referrerpolicy="strict-origin-when-cross-origin" src="https://www.youtube-nocookie.com/embed/bDRo7Cf7x1o?autoplay=0&amp;controls=1&amp;end=0&amp;loop=0&amp;mute=0&amp;start=0" style="position: absolute; top: 0; left: 0; width: 100%; height: 100%; border:0;" title="YouTube video"></iframe> </div> <ul> <li>PyTorch &amp; Lightning AI Meetup: Matrix Multiplication Assembly Instructions. London, UK. <a href="https://www.meetup.com/london-pytorch-meetup/events/305522836">Event</a>. <a href="https://youtu.be/bDRo7Cf7x1o">YouTube</a>.</li> <li>OpenUK 2025: Linux Kernel 6 - Path to 10x Faster Databases and Networking. London, UK. <a href="https://youtu.be/xzFYuTqGd6o">YouTube</a>.</li> <li>PyTorch Meetup 21 at Databricks: Scaling Vector Search Up &amp; Out with Spark. London, UK. <a href="https://www.meetup.com/london-pytorch-meetup/events/310701289">Event</a>. <a href="https://youtu.be/t5PHN1W92pU">YouTube</a>.</li> <li>OpenUK 2025: Democratizing AI - Optimizing Matrix Multiplications on Intel, Apple, AMD, NVIDIA &amp; AWS Chips. London, UK. <a href="https://youtu.be/Qujweq6Gf5A">YouTube</a>.</li> <li>PyData London 101: USearch - the Search Engine Behind Most New RAG Pipelines. London, UK. <a href="https://www.meetup.com/pydata-london-meetup/events/311635959">Event</a>.</li> <li>C++ &amp; Rust Cross-over Meetup: Writing &ldquo;Less Slow&rdquo; C++. London, UK. <a href="https://www.meetup.com/cpplondon/events/310272299">Event</a>.</li> </ul> <h2 id="2024">2024</h2> <div style="position: relative; padding-bottom: 56.25%; height: 0; overflow: hidden;"> <iframe allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share; fullscreen" loading="eager" referrerpolicy="strict-origin-when-cross-origin" src="https://www.youtube-nocookie.com/embed/LPv7QybMPxU?autoplay=0&amp;controls=1&amp;end=0&amp;loop=0&amp;mute=0&amp;start=0" style="position: absolute; top: 0; left: 0; width: 100%; height: 100%; border:0;" title="YouTube video"></iframe> </div> <ul> <li>ScyllaDB P99 Conf: Internet-Scale Semantic, Structural, and Text Search in Real Time. <a href="https://www.p99conf.io/">Event</a>. <a href="https://youtu.be/yn87sxRsOj0">YouTube</a>.</li> <li>UC Berkeley Open Source AI Day: Open Source Search: Two Decades of Bad Design Decisions &amp; Legacy Software. <a href="https://lu.ma/71y9vyb2?tk=7HrekN">Event</a>. <a href="https://youtu.be/LPv7QybMPxU">YouTube</a>.</li> <li>Arize Observe 2024. <a href="https://arize.com/observe-2024/">Event</a>.</li> <li>Neural Search Podcast: JIT Assembly to Build Exascale AI Infrastructure. <a href="https://youtu.be/zFq4-198OpQ">YouTube</a>.</li> <li>Attention Heads Podcast: Large scale data processing for AI apps. <a href="https://youtu.be/p96nkMM7wnM">YouTube</a>.</li> <li>Zaiste Programming Podcast: Unlocking the Future of AI with Open Source. <a href="https://youtu.be/D7pCY2ySicM">YouTube</a>.</li> <li>Multimodal Visual Question Answering. <a href="https://voxel51.com/computer-vision-events/may-30-2024-ai-machine-learning-data-science-meetup/">Event</a>. <a href="https://youtu.be/q_WWtZp4vgg">YouTube</a>. 👯‍♂️</li> </ul> <h2 id="2023">2023</h2> <div style="position: relative; padding-bottom: 56.25%; height: 0; overflow: hidden;"> <iframe allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share; fullscreen" loading="eager" referrerpolicy="strict-origin-when-cross-origin" src="https://www.youtube-nocookie.com/embed/UMrhB3icP9w?autoplay=0&amp;controls=1&amp;end=0&amp;loop=0&amp;mute=0&amp;start=0" style="position: absolute; top: 0; left: 0; width: 100%; height: 100%; border:0;" title="YouTube video"></iframe> </div> <ul> <li>AI.dev Linux Foundation Conference: Retrieval Augmentation and Semantic Search at Scale. San Jose, California, US. <a href="https://aidevcass23.sched.com/event/1VRvK">Event</a>. <a href="https://youtu.be/ODTpIbJ-Vks">YouTube</a>.</li> <li>All Things Open Conference: Bird&rsquo;s Eye View of Open-Source AI Infrastructure. Raleigh, North Carolina, US. <a href="https://2023.allthingsopen.org">Event</a>. <a href="https://drive.google.com/file/d/12bSVtE0ruQ_6lQSRNZN6juS2ybYL9T3S/view?usp=sharing">Slides</a>. <a href="https://www.youtube.com/watch?v=PQKYc0zK0iU">YouTube</a>.</li> <li>UC Berkeley Sky Lab Seminar: Vector Search at Scale - Bottlenecks and Solutions. Berkeley, California, US. <a href="https://sky.cs.berkeley.edu/events/sky-seminar-ashot-vardanian-unum-vector-search-at-scale-bottlenecks-and-solutions/">Event</a>.</li> <li>Cloud Native London: Future of Open-Source AI Infrastructure. London, UK. <a href="https://www.meetup.com/cloud-native-london/events/292727770/">Event</a>.</li> <li>Highload++ Conference: Vector Search and Databases at Scale. Belgrade Serbia. <a href="https://highload.rs/2023/abstracts/9770">Event</a>. <a href="https://drive.google.com/file/d/11M51Jw9UdEmzHDTGZmn4n3bxgTcQt3sw/view?usp=sharing">Slides</a>. <a href="https://www.youtube.com/watch?v=UMrhB3icP9w&amp;t=65s">YouTube</a>.</li> <li>Python SF Group: Accelerated Datascience Libraries and Where to Find Them. Sentry HQ, San Francisco, California, US. <a href="https://www.meetup.com/sfpython/events/skwnctyfchbnb/">Event</a>. <a href="https://youtu.be/L9ELuU3GeNc">YouTube</a>.</li> <li>CppCast Podcast #359: On AI Infrastructure. <a href="https://cppcast.com/ai_infrastructure/">Event</a>. <a href="https://open.spotify.com/episode/0GBepAsjOFerG9bT20WmFw">Spotify</a>. <a href="https://podcasts.apple.com/us/podcast/ai-infrastructure/id968703120?i=1000611006222">Apple Podcasts</a>. <a href="https://podcasts.google.com/feed/aHR0cHM6Ly9jcHBjYXN0LmNvbS9mZWVkLnJzcw/episode/ZjgwNzRkZmItNTUzNC00N2QwLWFjNDctZmNmNGRmMTc1NzQ1">Google Podcasts</a>.</li> </ul> <div style="position: relative; padding-bottom: 56.25%; height: 0; overflow: hidden;"> <iframe allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share; fullscreen" loading="eager" referrerpolicy="strict-origin-when-cross-origin" src="https://www.youtube-nocookie.com/embed/PQKYc0zK0iU?autoplay=0&amp;controls=1&amp;end=0&amp;loop=0&amp;mute=0&amp;start=0" style="position: absolute; top: 0; left: 0; width: 100%; height: 100%; border:0;" title="YouTube video"></iframe> </div> <ul> <li>Amazon AWS Podcast #32: Can you make a database 6-7 times faster? <a href="https://open.spotify.com/episode/7CsVxDOq8nYEBrQxRExM56&amp;nd=1">Spotify</a>. <a href="https://www.podbean.com/media/share/pb-vqhii-13e0414">Podbean</a>. <a href="https://podcasts.apple.com/by/podcast/032-%D0%BC%D0%BE%D0%B6%D0%BD%D0%BE-%D0%BB%D0%B8-%D1%83%D1%81%D0%BA%D0%BE%D1%80%D0%B8%D1%82%D1%8C-%D0%B1%D0%B0%D0%B7%D1%83-%D0%B4%D0%B0%D0%BD%D0%BD%D1%8B%D1%85-%D0%B2-6-7-%D1%80%D0%B0%D0%B7/id1600771698?i=1000608732451">Apple Podcasts</a>. <a href="https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkLnBvZGJlYW4uY29tL2F3c25hcnVzc2tvbS9mZWVkLnhtbA/episode/YXdzbmFydXNza29tLnBvZGJlYW4uY29tL2M0YjY3NzZiLTdkN2MtMzEzYS1hYzQwLWI5ZWIyNjUwM2ExMw?sa=X&amp;ved=0CAUQkfYCahcKEwjAjJ_X6bD-AhUAAAAAHQAAAAAQAQ">Google Podcasts</a>. 🇷🇺</li> <li>Attention Heads Podcast #4: Large scale data processing for AI apps. <a href="https://youtu.be/p96nkMM7wnM">YouTube</a>.</li> <li>DigiTech Conference: On deep tech startups and the development of the industry in Armenia. Yerevan, Armenia. <a href="https://www.digitec.am/ashot-vardanian">Event</a>. <a href="https://youtube.com/watch?v=V3L-O_qv7uU">YouTube</a>. 🗣️</li> <li>EVN Disrupt Podcast: Building AI While Embracing the Unorthodox. <a href="https://evnreport.com/podcasts/evn-disrupt/ashot-vardanyan-building-ai-while-embracing-the-unorthodox/">Event</a>. <a href="https://www.youtube.com/watch?v=mvpyJLW2lZI">YouTube</a>. <a href="https://open.spotify.com/episode/71wdHxO4oqfRCUsoaF1J0D">Spotify</a>. <a href="https://podcasts.apple.com/am/podcast/ashot-vardanyan-building-ai-while-embracing-the/id1252212513?i=1000596262592">Apple Podcasts</a>. 🗣️</li> <li>Voxel 51 Meetup: Scaling Similarity Search with USearch. <a href="https://voxel51.com/blog/recapping-the-ai-machine-learning-and-data-science-meetup-dec-7-2023/">Event</a>. <a href="https://youtu.be/x10DpjeegQk">YouTube</a>.</li> </ul> <h2 id="2022">2022</h2> <div style="position: relative; padding-bottom: 56.25%; height: 0; overflow: hidden;"> <iframe allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share; fullscreen" loading="eager" referrerpolicy="strict-origin-when-cross-origin" src="https://www.youtube-nocookie.com/embed/ybWeUf_hC7o?autoplay=0&amp;controls=1&amp;end=0&amp;loop=0&amp;mute=0&amp;start=0" style="position: absolute; top: 0; left: 0; width: 100%; height: 100%; border:0;" title="YouTube video"></iframe> </div> <ul> <li><strong>Highload++: Designing the fastest ACID Key-Value Store</strong>. <a href="https://highload.am/2022/abstracts/9673">Event</a>. <a href="https://www.youtube.com/watch?v=ybWeUf_hC7o">YouTube</a>. <a href="https://drive.google.com/file/d/16gdazzt9DTpCWPuXBAV2JSe1NW-Y7HvQ/view">Slides</a>.</li> <li><strong>DataFest: 3M - Prospects and Challenges with Multi-Modal Models in AI Research</strong>. <a href="https://datafest.am">Event</a>. <a href="https://youtu.be/p3RMkiqd7vY">YouTube</a>. <a href="https://drive.google.com/file/d/166UgMRVM1ORJPWQ74oRc2UH-bKmPHbqI/view">Slides</a>.</li> <li><strong>PyData Conference: Accelerated Data Science Libraries</strong>. <a href="https://pydata.org/yerevan2022/">Event</a>. <a href="https://youtu.be/OxAKSVuW2Yk">YouTube</a>. <a href="https://drive.google.com/file/d/168_Ctx0n6Jtw7ufSlTL3skCZR--lw-C0/view">Slides</a>.</li> <li><strong>Global Innovation Forum: Life Altering Technologies</strong>. <a href="https://fast.foundation/gif/2022/">Event</a>. <a href="https://www.youtube.com/watch?v=EBh9_7o31bI&amp;t=24447s">YouTube</a>. 🗣️</li> <li><strong>AMD &amp; Xilinx: Persistent Memory Technologies Overview</strong>. <a href="https://amd.com">AMD</a>. <a href="https://www.xilinx.com">Xilinx</a>.</li> <li><strong>CppRussia: Role of C++ in Machine Learning discussion</strong>. <a href="https://youtu.be/gO_bVvIN7HM">YouTube</a>. 🇷🇺</li> <li>CppArm Meetup #3: From OpenCL, Thrust &amp; CUB to raw CUDA Kernels &amp; SyCL. <a href="https://github.com/unum-cloud/ParallelReductions">GitHub</a>.</li> <li>PyData Meetup #2: Fast Inference for Large Language Models with Vladimir Orshulevich. <a href="https://youtu.be/tKwL-Q7INnQ">YouTube</a>. 👯‍♂️</li> <li>CppArm Meetup #4: Unsafe Math, GCC Attributes, and Nifty Tricks for Google Benchmark. <a href="https://github.com/ashvardanian/BenchmarkingTutorial">GitHub</a>.</li> <li>CppRussia: A Practical Approach to Error Handling by Arno Schödl. <a href="https://youtu.be/zNbmFRaetTA">YouTube</a>. 👯‍♂️</li> <li>PYerevan Meetup #16: Accelerated Data-Science Tools Overview. <a href="https://youtu.be/coTgcwnzvAg">YouTube</a>.</li> <li>CppArm Meetup #5: Bindings 101 - CPython, cGo, and Java Native Interface. <a href="https://github.com/unum-cloud/ustore">GitHub</a>. <a href="https://youtu.be/psmfAg1Nc3s">YouTube</a>.</li> </ul> <h2 id="2021">2021</h2> <ul> <li><strong>Mars Podcast: On High-Performance Computing</strong>. <a href="https://youtu.be/yK4Bd-6Mxk0">YouTube</a>. 🇦🇲</li> <li>CppArm Meetup #2: Evolution - C++11, 14, 17, 20, 23, 26? <a href="https://youtu.be/jtttoxkjTIA">YouTube</a>.</li> <li>Code Republic: Peta-Scale software in 2021. <a href="https://youtu.be/8R-43hfnPHI">YouTube</a>. <a href="https://drive.google.com/file/d/166nCWQH1-5KIPNmN4rUzebAW7mi6_eY5/view">Slides</a>. 🇦🇲</li> <li>FM106.5: On the Gituzh Scientific Initiative. <a href="https://youtu.be/89eDghXaZjI">YouTube</a>. 🇦🇲 🗣️</li> <li>CppRussia: SIMD with EVE by Denis Yaroshevskiy. <a href="https://youtu.be/CV0e-2a_dTI">YouTube</a>. 👯‍♂️</li> </ul> <h2 id="2020">2020</h2> <ul> <li><strong>CppRussia Conference: SIMD = Performance you have already paid for</strong>. <a href="https://2020.cppconf-piter.ru/2020/spb/talks/23g3egeumhe3p4fd66pbar/">Event</a>. <a href="https://github.com/ashvardanian/SubstringSearchBenchmark">GitHub</a>. <a href="https://youtu.be/6Sh9QWdzo58">YouTube</a>. <a href="https://drive.google.com/file/d/16BsyqGWjpNfqG0vAb21l0eySbChC_njJ/view">Slides</a>. 🇷🇺</li> <li><strong>CppArm Meetup #1: SIMD, Frequency Scaling Licenses and Speculative Execution</strong>. <a href="https://github.com/ashvardanian/CppBenchSubstrSearch">GitHub</a>. <a href="https://youtu.be/ft51yJ9mDcc?t=140">YouTube</a>.</li> <li>Pure Virtual Cast #4: Conversing about High-Performance Computing. <a href="https://youtu.be/dCdBFB4LDjw">YouTube</a>. 🇷🇺</li> <li>Artsakh Must Be Independent. <a href="https://youtu.be/sN8CsCgDlHY">YouTube</a>. 🗣️</li> </ul> <h2 id="2019">2019</h2> <div style="position: relative; padding-bottom: 56.25%; height: 0; overflow: hidden;"> <iframe allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share; fullscreen" loading="eager" referrerpolicy="strict-origin-when-cross-origin" src="https://www.youtube-nocookie.com/embed/AA4RI6o0h1U?autoplay=0&amp;controls=1&amp;end=0&amp;loop=0&amp;mute=0&amp;start=0" style="position: absolute; top: 0; left: 0; width: 100%; height: 100%; border:0;" title="YouTube video"></iframe> </div> <ul> <li><strong>CppRussia Conference: Deep dive into GPGPU programming</strong>. <a href="https://cppconf-piter.ru/en/2020/spb/talks/23g3egeumhe3p4fd66pbar/?fbclid=IwAR26hl3tEhw1os0J6oLzsVPTOAuSGkZIMzwq689tEq8NH5_V7b3MHV8f_zU">Event</a>. <a href="https://github.com/ashvardanian/SandboxGPUs">GitHub</a>. <a href="https://youtu.be/AA4RI6o0h1U">YouTube</a>. <a href="https://drive.google.com/file/d/16AicAl99t3ZZFnza04Wnw_Vuem0w8lc7/view">Slides</a>.</li> <li><strong>CppBayArea: AI and Computational Graphs in C++</strong>. <a href="https://www.meetup.com/cpp-bay-area/events/261294493/">Event</a>. <a href="https://github.com/ashvardanian/NeuralSTL">GitHub</a>.</li> <li>JetBrains HQ: Efficient GPGPU Programming. <a href="https://www.jetbrains.com">Event</a>. <a href="https://github.com/ashvardanian/SandboxGPUs">GitHub</a>. <a href="https://youtu.be/BUtHOftDm_Y">YouTube</a>.</li> </ul>