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AI-native software engineering may be closer than developers think

CIO Business Intelligence

Organizations and vendors are already rolling out AI coding agents that enable developers to fully automate or offload many tasks, with more pilot programs and proofs-of-concept likely to be launched in 2025, says Philip Walsh, senior principal analyst in Gartner’s software engineering practice. This technology already exists.”

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Cisco takes inspiration from Iron Man for its AI-driven platform engineer

Network World

The aim is to help address the growing complexity of platform and infrastructure engineering, and the inspiration is from the Iron Man superhero franchise: Tony Starks superlative natural-language computer system is called Just A Rather Very Intelligent System ( J.A.R.V.I.S. ). Platform engineering has hit a crisis point of complexity.

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Leading high-performance engineering teams: Lessons from mission-critical systems

CIO Business Intelligence

As leaders in engineering, we are ultimately responsible for the quality of our product, the most important factor for user happiness and business success. Leading a group of highly skilled and intellectual engineers requires more than just engineering competence; it also means guiding systems and people to be flexible.

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Comprehensive data management for AI: The next-gen data management engine that will drive AI to new heights

CIO Business Intelligence

Imagine that you’re a data engineer. These challenges are quite common for the data engineers and data scientists we speak to. An enhanced metadata management engine helps customers understand all the data assets in their organization so that they can simplify model training and fine tuning. Seamless data integration.

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How to Achieve High-Accuracy Results When Using LLMs

Speaker: Ben Epstein, Stealth Founder & CTO | Tony Karrer, Founder & CTO, Aggregage

In this new session, Ben will share how he and his team engineered a system (based on proven software engineering approaches) that employs reproducible test variations (via temperature 0 and fixed seeds), and enables non-LLM evaluation metrics for at-scale production guardrails.

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Cadence debuts Nvidia-powered supercomputer to accelerate enterprise engineering, biotech

Network World

Cadence Design Systems on Wednesday introduced the Millennium M2000, a supercomputer powered by Nvidias latest Blackwell GPUs , aimed at accelerating AI-enabled simulations for chip design, aerospace engineering, and drug discovery. GPUs are seen as the most efficient compute engines capable of managing these workloads at scale.

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8 network observability certifications to boost IT operations skills

Network World

Cisco Certified Network Professional (CCNP) Overview: CCNP certifications , such as Enterprise, Data Center, or Service Provider, will equip network engineers with the skills and knowledge to design, implement, and troubleshoot complex network infrastructure, including several of the aspects that directly contribute to observability.

Network 365
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Autonomous AI Agents Are the Future of Procurement and Supply Chain Operations

These agents self-reflect with a memory engine that allows them to learn from mistakes. Unlike LLM-based generative AI tools such as ChatGPT, these AI agents do not require prompts from humans.

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Agent Tooling: Connecting AI to Your Tools, Systems & Data

Speaker: Alex Salazar, CEO & Co-Founder @ Arcade | Nate Barbettini, Founding Engineer @ Arcade | Tony Karrer, Founder & CTO @ Aggregage

As an engineering leader, it can be challenging to make sense of this evolving landscape, but agent tooling provides such high value that it’s critical we figure out how to move forward. There’s a lot of noise surrounding the ability of AI agents to connect to your tools, systems and data.

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Generative AI Deep Dive: Advancing from Proof of Concept to Production

Speaker: Maher Hanafi, VP of Engineering at Betterworks & Tony Karrer, CTO at Aggregage

💡 This new webinar featuring Maher Hanafi, VP of Engineering at Betterworks, will explore a practical framework to transform Generative AI prototypes into impactful products! There's no question that it is challenging to figure out where to focus and how to advance when it’s a new field that is evolving everyday.

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Improving the Accuracy of Generative AI Systems: A Structured Approach

Speaker: Anindo Banerjea, CTO at Civio & Tony Karrer, CTO at Aggregage

Using this case study, he'll also take us through his systematic approach of iterative cycles of human feedback, engineering, and measuring performance. . 💥 Anindo Banerjea is here to showcase his significant experience building AI/ML SaaS applications as he walks us through the current problems his company, Civio, is solving.

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LLMs in Production: Tooling, Process, and Team Structure

Speaker: Dr. Greg Loughnane and Chris Alexiuk

Greg Loughnane and Chris Alexiuk in this exciting webinar to learn all about: How to design and implement production-ready systems with guardrails, active monitoring of key evaluation metrics beyond latency and token count, managing prompts, and understanding the process for continuous improvement Best practices for setting up the proper mix of open- (..)

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12 Considerations When Evaluating Data Lake Engine Vendors for Analytics and BI

To do so, modern enterprises leverage cloud data lakes as the platform used to store data for analytical purposes, combined with various compute engines for processing that data. Businesses today compete on their ability to turn big data into essential business insights.

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Top Considerations for Building an Open Cloud Data Lake

Increasingly, enterprises are leveraging cloud data lakes as the platform used to store data for analytics, combined with various compute engines for processing that data. How cloud data lake engines enable a better balance between data warehouse investments versus those in the cloud data lake

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Discover How Senior Technology Leaders Can Secure the Budget That They Need

Speaker: Kevin Goldsmith, Chief Technology Officer at Anaconda | Peyman Pouryekta, CEO and Technology Advisor | Bob Webber, VP Product Flow Optimization, Construx

This can be challenging, as engineering is often seen as a cost center, making it difficult to gain management buy-in for strategic investments. Quantify the value of the software that engineering produces. By the end of this session you will learn how to: Strategically invest in technology. Determine the success of an investment.