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Running Reflection 70B in moved to: @lmstudio , and the reflection technique is certainly making the model think more. Feels its getting to a strange but arguably correct answer by brute force. The analysis of the interior shape of the cup is funny though.

you don’t need elegantly solve intelligence on paper when deep networks are just begging to learn

Seeing stellar performance with HEAVY.AI HeavyDB on the Star Schema Benchmark (1000 GB) on the NVIDIA GH200 Grace Hopper superchip and a 8XA100 GPU instance on Vultr Cloud. It takes only 1.5 seconds to run all 13 queries, 50X+ faster than other data warehouses for the price.

We launched HeavyIQ earlier this year to our users to effortlessly generate SQL and visualizations in the HEAVY.AI platform using natural language. But now with the new LLM_TRANSFORM SQL operator, you can use the power of the HeavyIQ Large Language Model to add fuzzy logic to

Excited to explore the incredible performance of NVIDIA Grace Hopper for data analytics workloads with our friends from Vultr and NVIDIA Data Center. Come join the webinar this Halloween to learn more.

At HEAVY.AI we recently benchmarked GPU-accelerated HeavyDB against an array of CPU data warehouses, including Snowflake, Databricks, BigQuery, and Redshift, seeing over 100X speedups in some cases. Included in our testing was the new NVIDIA ARM-based Grace Hopper GH200

Come check out a webinar I'll be giving with NVIDIA and Vultr tomorrow about the revolutionary performance of the Grace Hopper Superchip. With fast NVLink between CPU and GPU, we are finally unchained from the "thin straw" of PCIe.

#30DayMapChallenge Day 1: Points AIS transmissions from cargo ships and tankers loitering near the Port of Long Beach, showing the ship backlog during the supply chain crisis of 2021. Source: 20.4 billion AIS data points from Marine Cadastre, shown in HEAVY.AI.

#30DayMapChallenge Day 3: Polygons New Oak Ridge Lab US buildings dataset, complete with addresses and height data. Here are building footprints in the Philadelphia area, colored by height in HEAVY.AI.

Was super excited this morning to see Location.Foursquare had open sourced a dataset over 100M POIs. I immediately it into HEAVY.AI and am having a lot of fun exploring the data, it looks fantastic both in terms of coverage and accuracy.

I've been diving deeper into the Location.Foursquare Places dataset that was released two weeks ago, and am finding it great not only for accessing individual POIs, but also for performing large-scale analysis of geographic trends. Here I'm using HEAVY.AI to join the Places dataset to

We are excited to announce the availability of the HEAVY.AI GPU-accelerated analytics platform on the Nvidia Grace Hopper GH200 Superchip, offering customers significantly better performance at lower cost. businesswire.com/news/home/2025…

Interactively explore over 20 billion records of ship AIS data in our new demo of HEAVY.AI on the NVIDIA Grace Hopper Superchip, running in Vultr Cloud. See our blog for more info: heavy.ai/blog/interacti…

We're proud to announce a new partnership with Ookla, a leader in network intelligence. With Ookla's wide array of unique crowdsourced and drive test data, paired with HEAVY.AI, organizations can optimize, plan, and pinpoint issues in their networks faster than ever before.

Enabling real-time geospatial joins at scale has always been a key goal of ours at HEAVY.AI. Check out our blog benchmarking geo join performance in GPU-accelerated HeavyDB against Postgres, DuckDB, Snowflake, BigQuery, and Redshift.

We recently expanded our support for the Uber H3 hierarchical geospatial index to HeavyDB, allowing users to easily aggregate, visualize, and join data using the H3 grid. Check out our new blog to learn more and see examples of this powerful new capability in action.