Add post announcing the v2024 Array API Standard release

PR-URL: #28
Reviewed-by: Evgeni Burovski

Author: kgryte

content/blog/array_api_v2024_release.md

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+date = "2025-02-27T08:00:00+00:00"
+author = "Athan Reines"
+title = "2024 release of the Array API Standard"
+tags = ["APIs", "standard", "consortium", "arrays", "community"]
+categories = ["Consortium", "Standardization"]
+description = "The 2024 revision of the array API standard has been finalized and is ready for adoption by conforming array libraries."
+draft = false
+weight = 30
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+
+Another year, another milestone! We're excited to announce the release of the
+2024 revision of the Array API Standard, the latest iteration of our ongoing
+efforts to unify and standardize array programming across the PyData ecosystem.
+Since the standard's inception, our goal has been to facilitate
+interoperability between array libraries and enable a more consistent and
+predictable developer experience. This year's update continues that mission
+with key enhancements, new features, and clarifications that reflect the needs
+of the community.
+
+## Key Enhancements in v2024.12
+
+### Scalar Argument Support
+
+Previously, binary element-wise functions, such as `add`, `mul`, and others,
+required both input arguments to be arrays. This constraint has now been
+relaxed: scalars are now allowed as arguments, as long as at least one argument
+is an array. This change aligns with common practices in numerical computing
+workflows and makes it easier to write concise, readable code.
+
+### Integer Array Indexing
+
+Portable indexing semantics just got more powerful! The 2024 revision of the
+standard introduces support for indexing an array using tuples consisting
+solely of integers and integer arrays. This feature—a subset of NumPy's
+vectorized fancy indexing—was a highly requested addition from downstream
+users. It enables efficient random sampling and more flexible multi-dimensional
+indexing, making it easier to work with large datasets and tensors.
+
+For more details, see [_Integer Array Indexing_](https://data-apis.org/array-api/latest/API_specification/indexing.html#integer-array-indexing)
+in the specification.
+
+### New API Additions
+
+Several new APIs have been introduced in this release to expand functionality
+and improve usability:
+
+-   `count_nonzero`: counts the number of nonzero elements in an array.
+-   `cumulative_prod`: computes the cumulative product along a specified axis.
+-   `take_along_axis`: selects elements from an array using indices along a
+    given axis.
+-   `diff`: computes the discrete difference between consecutive elements.
+-   `nextafter`: returns the next representable floating-point value in the
+    direction of another floating-point value.
+
+These additions further close the gap between the Array API Standard and
+established numerical computing libraries.
+
+### Breaking Changes
+
+With progress comes necessary refinements. This year's update includes two
+significant breaking changes:
+
+-   **Device-aware type promotion**: The guidance for `result_type` and `can_cast`
+    has been updated to require that type promotion rules account for device
+    contexts when at least one operand is an array. This ensures that type
+    promotion can be correctly handled across different hardware environments
+    and accurately reflect device capabilities.
+-   **Refined handling of Python complex scalars**: Previously, for binary
+    operations involving an array and a Python scalar, the standard required
+    that all scalar values be automatically converted to zero-dimensional
+    arrays of the same type as the array operand. Now, if a Python `complex`
+    scalar is used in an operation (e.g., `x * 1j`), the real-valued array
+    operand should be promoted to a complex floating-point type of the same
+    precision as the original array operand. This change better aligns with
+    practical use cases involving complex numbers and helps improve developer
+    ergonomics.
+
+### Specification Clarifications
+
+Standards evolve not just through feature additions but also through
+refinements. Over the past year, we've worked closely with implementers and
+downstream users to resolve ambiguities in the specification. These
+clarifications ensure that adopting the standard is as seamless as possible and
+that behavior is well-defined across implementations.
+
+## Looking Ahead
+
+The 2024 revision of the Array API Standard represents another step forward in
+making array interoperability a reality across the Python ecosystem. Every
+iteration of the standard reflects deep collaboration across the PyData
+community, with contributions from library maintainers, researchers, and
+practitioners.
+
+We encourage all implementers to adopt the latest version and welcome feedback
+from the community. If you're interested in contributing to future discussions,
+check out the [specification repository](https://github.com/data-apis/array-api)
+and get involved!
+
+For full details on this release, see the [changelog](https://data-apis.org/array-api/latest/changelog.html#v2024-12).
+
+Here's to another year of advancing the frontier of array and tensor computing
+in Python!