How is Jazz a solution

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Our Purpose in 2016
Jazz was a tensor storage before it was cool. Back in 2016, we were motivated by the need for lightning-fast data retrieval in backend applications, where every millisecond mattered. Our systems demanded not just efficient data storage but also robust backend computation to process complex operations seamlessly. Jazz emerged as a solution to bridge these needs, combining speed and computational capability in a way that felt ahead of its time.
Bebop-25: Redefining Machine Understanding Through Iterative Execution
The transition to Bebop-25 marked a pivotal moment for us, driven by the realization that true machine understanding required more than conventional approaches to automated code generation. As Jazz evolved, becoming open source, we turned our focus to enabling it to write, run, and evaluate code autonomously. This wasn’t about targeting traditional software development but fulfilling the foundational need for machines to grasp and execute programs in ways that mirror human intent. Over time, the concept of Bebop, though always carrying the same name, took on many iterations before solidifying as Bebop-25—a culmination of years of research and discovery.
Tackling the challenge of searching within the space of possible programs meant confronting a problem of combinatorial explosion. In this quest, we encountered a need for something that simply did not exist. Reflecting on historical ingenuity, we drew inspiration from Antonio Gaudí, the Spanish architect who designed the ambitious Sagrada Familia over a century ago. To calculate its complex curves before the age of computers, he created an inverted physical model using strings and weighted bags, letting physics solve the equations of his design. In a similar spirit, we realized that solving our problem required not just thinking outside the box but flipping it upside down—embedding program execution as an integral part of the search process, rather than an isolated step that follows program creation.
This shift in thinking became the cornerstone of Bebop-25. By integrating execution into the search itself, we crafted a system that could explore, test, and refine potential solutions in real-time, emulating a kind of “live computation”. This paradigm redefined how we approached automated code generation and problem-solving, enabling us to move beyond static workflows to a dynamic, iterative process. Bebop-25 is more than just a system; it represents a philosophy of embracing unconventional approaches to drive innovation in machine understanding.

Bebop-25 has introspection and composition at its core. By representing everything as a computational graph, it inherently understands dependencies, enabling seamless transformations such as converting a method of a class into a standalone function or merging multiple functions into a cohesive unit. This natural handling of dependencies extends beyond structure to behavior, making the system remarkably adaptable. On top of this, the resolver/compiler paradigm empowers Bebop-25 to compose code in a manner analogous to how we construct natural language—blending smaller, meaningful units into larger, coherent expressions. This approach bridges the gap between human intent and machine execution, making Bebop-25 not only a tool but a true partner in problem-solving.</b>
Summarizing Jazz 1.25.x
Jazz is | |
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Native tensors and native tuples | Built-in support for efficient data structures. |
Persistence | Memory-mapped storage for high-performance data access. |
In RAM retrieval | Uses optimized C structures for rapid data access. |
Data abstraction | Spaces support, sharding, embeddings, time series, and more. |
Communication | Integrates via bash, ZeroMQ and REST. |
Computation | Leverages onnx-runtime for optimized execution. Compiled from Bebop-25 or written by Keras, Pytorch, ... |
Code generation | Generates Bebop-25 automatically by a resolver, runs and evaluates. |
Monolith design | An all-in-one C++ framework for comprehensive functionality. |
Jazz is a platform built for unmatched speed and innovation, with code creation, introspection and composition embedded at its core. It redefines what’s possible, making it a foundation for the future of intelligence engineering.