Firat Kalsin

Serial Entrepreneur and Investor, proud father of 2, addicted to sailing and crystal clear waters of the Med

[Rescale @RescaleInc]

What if aerospace teams could get more value from the simulation data they already have?

Rescale will be at Farnborough International Airshow 2026 TODAY to show how connected simulation, HPC, data, and AI can help engineering teams modernise product development, reduce manual workflow friction, and explore more design candidates with less complexity.

The results can be significant: Rescale highlights 4x–8x more design candidates explored and a 78% reduction in R&D cycle time on its Farnborough event page.

Boom Supersonic’s case study adds a real-world example: the company used Rescale’s cloud HPC platform from day one, gained virtually unlimited compute capacity, and scaled simulations on demand with pay-as-you-go infrastructure.

If you’re attending the show, book time with the team onsite and explore what AI-first engineering could look like for your organisation.

Learn more: https://t.co/CIq5K31BkG

#FIA2026 #FarnboroughInternationalAirshow #AerospaceInnovation #CFD #CAE #HPC #AIforEngineering #Rescale

[LimaCharlie @limacharlieio]

Our LimaCharlie 101 virtual workshop is this Wednesday July 22nd, covering everything from EDR deployment to automated threat response.

You'll spend two hours working directly inside the platform, deploying EDR agents, analyzing telemetry to surface indicators of compromise, and writing detection and response rules across the threat spectrum from commodity malware to APTs.

The session also covers threat intelligence integration, so you can operationalize external feeds directly into your detections, and YARA rule creation for malware identification.

Save your spot: https://t.co/rXESIS695U

[LimaCharlie @limacharlieio]

Most AI security products are black boxes. You see the output. You don't see what the agent did to get there.

With Grid, every action an AI operator takes is logged, auditable, and inspectable through the same API surface that created it:

> Detection rules written
> Response actions executed
> Cases opened
> Approvals requested and granted

Maxime walks through the AI workbench in the full session, showing exactly how teams maintain visibility and control over every operator decision.

See it for yourself: https://t.co/IZKdrlLlhG

[Rescale @RescaleInc]

Move simulation data between your desktop and the cloud faster with Rescale Interlink. This open-source hybrid CLI and GUI tool allow engineers to manage files and jobs on Rescale from one lightweight application.

FIPS 140-3 compliant and available on Windows, Mac, and Linux, Interlink supports multithreaded parallel transfers, a visual file browser, auto-download of completed job results, and full job submission.

For engineers working in cloud HPC, data movement and job tracking can eat up time across every simulation campaign. Interlink consolidates those tasks into a single tool that works from both the command line and a desktop GUI.

The file browser lets engineers navigate local and Rescale storage side by side, while auto-download monitors completed jobs and pulls results to a designated folder without manual intervention. It is open source on GitHub, actively community-contributed, and already in production use at enterprise engineering organizations.

Explore the public repo and try it: https://t.co/CqqVlKgnX0

#DigitalEngineering #CloudHPC #SimulationWorkflows #OpenSource #EngineeringProductivity

[Rescale @RescaleInc]

Engineering data rarely lives in one place, and that fragmentation slows simulation teams down.

Rescale’s data connectors help engineers browse, search, and use data from AWS S3, Azure Blob, and SharePoint directly in jobs and AI-assisted workflows, without replacing existing systems or manually moving files around. It is a practical step toward making engineering data more usable across the Rescale platform, including for agentic digital engineering workflows.

Read the full blog:
https://t.co/HOSEVi9VGC

#DigitalEngineering #SimulationData #AgenticEngineering #EngineeringAI #HPC

[LimaCharlie @limacharlieio]

Most AI in security workshops end with a slide deck and a product pitch. This one ends with something you built.

We're hosting a free, hands-on workshop on Wednesday, August 5 at Black Hat alongside @BHinfoSecurity and @DDI_Training.

Six hours. Real infrastructure. No marketing deck. Food and drinks included.

Maxime Lamothe-Brassard opens at noon with a short technical talk on the headless SOC, then hands the day to the instructors.

Ken Westin and Chris Botelho will lead hands-on sessions for all skill levels. From first AI agent deployment to advanced multi-agent hunting pipelines.

Hayden Covington, Eric Capuano, and Whitney Champion will run an open threat hunting lab all afternoon on live infrastructure where every agent is readable and every action is auditable.

Space is limited. Reserve your spot: https://t.co/GD0cVcAil4

[Rescale @RescaleInc]

Resolve simulation failures in minutes, not hours.

Rescale’s job troubleshooting agent analyzes solver logs, pinpoints the failure, explains what went wrong in plain language, and recommends corrective actions within the Rescale Assistant. Engineers review and approve fixes before resubmission, which keeps human judgment in the loop while removing the manual overhead of failure diagnosis.

For simulation-intensive teams, diagnosing failed runs can quietly drain engineering throughput. Engineers often spend hours parsing solver logs, cross-referencing error codes, and testing configuration changes before they find the root cause. That time adds up across every campaign and takes capacity away from design exploration and analysis.

The impact is especially high during design-of-experiments campaigns and in multi-solver environments, where one failed run can stall downstream work and detailed diagnostic knowledge is hard to maintain across every application. Agent-driven triage inside the platform helps engineers focus on engineering decisions, not log parsing.

Learn more about Rescale specialized agents for common engineering use cases: https://t.co/A8WgTc6RCn

#DigitalEngineering #Simulation #AgenticAI #EngineeringProductivity #CAE

[Rescale @RescaleInc]

Aerospace teams are being asked to move faster with fewer resources while making more design decisions earlier in the programme lifecycle.

At Farnborough International Airshow 2026 next week, Rescale is meeting with aerospace and defence teams to talk about a practical path to AI-first engineering, connecting simulation, data, AI, and HPC in one workflow to automate manual work, expand design exploration, and improve engineering productivity without disrupting trusted tools and processes.

Boom Supersonic is a strong example of what this can look like in practice. Boom simulated its XB-1 entirely on Rescale, used cloud HPC to run highly compute-intensive jobs in minutes to hours, and enabled each engineer to evaluate 100 design configurations at once with more than 6x speedup versus a typical workstation.

If you’ll be at Farnborough on July 20–24 in Farnborough, UK, come meet the Rescale team onsite.

Learn more: https://t.co/CIq5K31BkG

#FIA2026 #FarnboroughAirshow #Aerospace #Engineering #Simulation #HPC #AI #DigitalEngineering

[Rescale @RescaleInc]

Rescale's Q2 newsletter is live.

If you want a practical view of how AI-first engineering is showing up in production workflows, this edition is worth a read. It highlights what's new across agentic digital engineering, AI physics, and compute economics on the Rescale platform, along with the outcomes these capabilities are designed to support.

Inside, you'll find a closer look at simulation-native agents for tasks like input validation, failure diagnosis, hardware configuration, and reporting, plus new AI physics capabilities that help teams turn simulation data into production-ready surrogate models.

It also includes proof points from the launch, including 30x cost-efficiency gains, 4x more design candidates evaluated per cycle, and 40% reduction in total compute spend, as well as resources like the Guide to AI-First Engineering and the on-demand webinar for teams looking to go deeper.

Read the Q2 newsletter: https://t.co/B5JmgA6MFO

#DigitalEngineering #AIFirstEngineering #AIPhysics #EngineeringSimulation #AgenticDigitalEngineering

[Rescale @RescaleInc]

Start training surrogate models faster with open-source AI datasets now available in Rescale AI Physics.

Engineers can now train models directly from the DrivAerML dataset, a subset of a high-fidelity open-source public dataset for automotive aerodynamics built from 500 parametrically morphed variants.

For teams exploring AI physics, this removes one of the first practical barriers to getting started. Instead of spending time generating their own simulation dataset before they can evaluate model training, users can begin from a curated dataset already available in the Rescale platform and move more quickly into experimentation, benchmarking, and workflow learning.

Datasets like this are especially useful for teams that want to evaluate surrogate modeling workflows, test model architectures, or build internal familiarity before committing their own simulation history to a training pipeline. It creates a more accessible entry point while keeping the workflow inside the Rescale platform.

Learn more about getting started with AI physics model training on Rescale: https://t.co/P0XulLOKkl

#AIPhysics #SurrogateModeling #DigitalEngineering #EngineeringAI #AutomotiveAerodynamics

[LimaCharlie @limacharlieio]

Automating security workflows usually means picking a platform and committing your stack to it.

Grid takes a different approach: connect a data source, define your approval thresholds, and AI operators run against your existing telemetry on a parallel track. Nothing in your environment moves.

That includes the exceptions. The requests that need a human call. The approvals that have to route through a specific channel. Grid handles the full workflow, your way.

The full session goes deeper on cross-tenant operations, audit trails, and how Grid continues to improve as you scale.

Catch the replay: https://t.co/7rI7nkUgOm

[Rescale @RescaleInc]

Recently in Tokyo, Rescale brought together technical leaders, engineers, and partners from across that ecosystem to explore what's possible when agentic digital engineering and AI physics come together on a unified platform built for the AI era.

The conversations were grounded in where R&D organizations are today, and where they need to go. Rescale COO Matt McKee and VP of Product Jacob Surber joined the Japan team to discuss how agentic digital engineering can automate complex simulation workflows, and how AI physics enables predictions at inference speed, expanding what engineering teams can explore without proportionally expanding the time or compute required.

Building the future of digital engineering takes collaboration across the simulation community, and the energy in the room reflected exactly that.

#DigitalEngineering #AgenticDigitalEngineering #AIPhysics #Simulation #CAE

—

先日東京にて、Rescaleはデジタルエンジニアリングのエコシステムから技術リーダー、エンジニア、そしてパートナー企業の皆様をお迎えするイベントを開催しました。AI時代のために開発された統合プラットフォーム（the Rescale platform）上で、エージェンティック・デジタルエンジニアリングとAI物理（AI physics）が融合したときに、どのような可能性が広がるのかを共に模索しました。

当日の議論は、研究開発（R&D）組織の現状と、今後目指すべき方向性を踏まえた極めて実践的なものとなりました。RescaleのCOOであるマット・マッキー（Matt McKee）と、プロダクト担当VPのジェイコブ・サーバー（Jacob Surber）が日本のチームに加わり、エージェンティック・デジタルエンジニアリングがいかに複雑なシミュレーション・ワークフローを自動化できるか、そしてAI物理がいかに推論速度での予測を可能にするかについてディスカッションを行いました。これにより、エンジニアリングチームは、必要な時間や計算リソースを比例的に増やすことなく、探索の幅を大きく広げることが可能になります。

デジタルエンジニアリングの未来を築くには、シミュレーション・コミュニティ全体のコラボレーションが欠かせません。会場の熱気は、まさにその強力な結束を反映したものでした。

[Rescale @RescaleInc]

Training accurate AI surrogate models for CFD and FEA gets harder when geometry is part of the problem. GeoTransolver helps engineering teams build high-accuracy models that can work with complex 3D geometries and unstructured meshes without losing the spatial relationships that matter for prediction quality.

Now available in Rescale AI Physics through the NVIDIA PhysicsNeMo library, GeoTransolver is a geometry-aware transformer architecture that uses GALE attention to model relationships across complex 3D geometries and unstructured meshes. It is built to generalize across changing operating conditions and learn transient, geometry-aware physical behavior across design variants.

Take a look at this animation: GeoTransolver on Rescale modeling a soccer ball’s contact and deformation to help determine whether a crossbar strike becomes a goal.

It’s the same kind of challenge teams face in external aerodynamics, thermal analysis, impact, deformation, and other workflows where small changes in geometry or initial conditions can lead to very different outcomes.

Learn more: https://t.co/f2BNUJMtjq

#AIPhysics #CFD #FEA #DigitalEngineering #SurrogateModeling

[Rescale @RescaleInc]

When prior simulation work is buried across storage buckets, wikis, and shared drives, engineers lose time retracing work instead of building on it. Simulation teams generate institutional knowledge in every program, from solver configurations and analysis results to validated methodologies and documented findings. The challenge is making that knowledge usable when it lives across disconnected systems.

Rescale now connects engineering data stored in AWS S3 and Azure Blob Storage directly to the Rescale Assistant through vectorized search. That gives engineers a way to ask natural language questions and get fast, contextually grounded answers drawn from their organization’s own data, rather than relying only on general AI knowledge or manual file searches. It turns scattered engineering data into searchable institutional knowledge teams can actually reuse.

In digital engineering workflows, this is especially useful when teams need to reference prior simulation results, revisit validated model configurations, or understand how similar engineering problems were approached in earlier programs.

For engineering teams, that means less time hunting for files and more time applying proven methods to the next problem through a conversational interface.

Learn more: https://t.co/P761AUZI8N

#DigitalEngineering #Simulation #EngineeringData #AI #Rescale

[Lisa Abramowicz @lisaabramowicz1]

This is the growing concern, that the US’s curbs on the latest Anthropic and OpenAI models will only accelerate a shift to cheaper, open-source Chinese models. Even if they’re not as good as the top US models yet, they’re good enough. (1/2) https://t.co/KDWmGsgdRf

[Dr. Bora Uygun 🦅 @bora_uygun]

lol 😂

[507 @e507]

Amerika 🇺🇸, fırsatlar ülkesi! Pratikte; göçmenler için "akraba ve arkadaşların -gel bizim sektörde çalış-" diyerek net sosyokültürel bağlar yarattığı bir ekonomik yapı. "Midye & Mardin" ilişkisini yeni kıtaya taşıyan etnik ağlar ve gizli giriş bariyerleri yarattıkları iş kolları:

1. Kaliforniya'daki donut'çıların %80'i Kamboçyalı. Chicago'daki Dunkin Donut'ların %95'i ise Hintlilere ait.
2. ABD'deki tüm motellerin %42'sini de Hintliler, özellikle Gujarati'ler işletir.
3. Tüm manikürcülerin yarısı Vietnamlıdır. Kaliforniya'da oran %80'e çıkar.
4. Detroit'teki marketlerin %90'ını Keldaniler işletir.
5. Kaliforniya tır şöförlerinin %40'ı Sih'tir.
6. Baltimore'daki içki dükkanlarının %90'ı Korelilere aittir.
7. New York'taki diner restoran sahiplerinin %60'ı Rum kökenlidir.
Bonus 🇬🇧: İngiltere'deki uyuşturucu ticareti Arnavutların, Hint restoranları Bangladeşlilerin, berberler ise Türklerin kontrolünde.

Kaynak: Beklenmedik etnik nişler
https://t.co/duabTYEMPD

[Rescale @RescaleInc]

When a simulation campaign ends, the engineering work may be done, but turning raw results into a structured, presentation-ready report still takes time most engineers do not have.

Rescale’s Report Generator Agent closes that gap by taking simulation results data and automatically generating a report aligned to a customer’s own reporting templates, including findings, relevant charts, and recommendations. The output is designed to be ready for stakeholders, without requiring engineering teams to manually assemble slides or summarize data after the fact.

That fits naturally into digital engineering workflows, where simulation is one input into a broader product development decision. When program managers, systems engineers, or design leads need to understand what a set of simulations found, report generation can happen in minutes rather than hours, in a format that is already familiar to the people reading it.

It’s a practical example of how Rescale applies agentic digital engineering on the Rescale platform to automate complex workflows while keeping the focus on higher-value engineering decisions.

Learn more: https://t.co/xS1z8EqrOf

#DigitalEngineering #AgenticAI #Simulation #EngineeringWorkflows #ProductDevelopment

[Rescale @RescaleInc]

As engineering gets more complex, the tools teams rely on need to evolve too.

AI is creating new ways to reduce friction in simulation workflows, speed up iteration, and help R&D teams move from idea to insight faster.

We put together a short eBook on what AI-first engineering can look like in practice.

Download it here: https://t.co/t5IN3Nlp9k

#AIEngineering #DigitalEngineering #Simulation #RAndD #EngineeringInnovation

[Behlül Özkan @BehlulOzkan]

Krizlere doğan, krizlerle büyüyen ve hayatta kalma mücadelesinde ayakta kalabilen halkımızın günün akışı içindeki krize müdahalesi.