Dynamic programming languages like Python and TypeScript allows developers to optionally define type annotations and benefit from the advantages of static typing such as better code completion, early bug detection.
However, retrofitting types is a cumbersome and error-prone process. To address this, we propose Type4Py , an ML-based type auto-completion for Python. It assists developers to gradually add type annotations to their codebases. In the following, I describe Type4Py’s pipeline, model, deployments, and the development of its VSCode extension and more.
Berlin-based Mobius Labs has closed a €5.2 million (~$6.1M) funding round off the back of increased demand for its computer vision training platform. The Series A investment is led by Ventech VC, along with Atlantic Labs, APEX Ventures, Space Capital, Lunar Ventures plus some additional angel investors.
The startup offers an SDK that lets the user create custom computer vision models fed with a little of their own training data — as an alternative to off-the-shelf tools which may not have the required specificity for a particular use case.
Let’s start with security. It’s at the forefront of many minds these days, with supply chain issues, cryptojacking and data breaches being common news stories. WebAssembly brings some big guns to the security fight in a number of ways, starting with its security sandbox.
When WASM is executed, the code is not given access to anything, including the network, file system or anything else out of the box. This is known as a deny-by-default security model. For the code running inside the WASM sandbox to interact with the outside world, it must be explicitly granted access to host functions.
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