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README.md

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 <img src="https://raw.githubusercontent.com/PennyLaneAI/pennylane/master/doc/_static/code.png" width="400px" align="right">
 
-- *Program quantum computers*. Build flexible quantum circuits with a wide range of state preparations, gates, and measurements. Run on high-performance simulators or various hardware devices, with advanced features like mid-circuit measurements and error mitigation.
+- <strong>*Program quantum computers*</strong>. Build quantum circuits with a wide range of state preparations, gates, and measurements. Run on [high-performance simulators](https://pennylane.ai/performance/) or various hardware devices, with advanced features like mid-circuit measurements and error mitigation.
 
-- *Integrate with Machine learning*. Integrate with **PyTorch**, **TensorFlow**, **JAX**, **Keras**, or **NumPy** to define and train hybrid models using quantum-aware optimizers and hardware-compatible gradients for advanced research tasks.
+- <strong>*Integrate with machine learning*</strong>. Integrate with **PyTorch**, **TensorFlow**, **JAX**, **Keras**, or **NumPy** to define and train hybrid models using quantum-aware optimizers and hardware-compatible gradients for advanced research tasks. [Quantum machine learning quick start](https://docs.pennylane.ai/en/stable/introduction/interfaces.html).
 
-- *Master quantum algorithms*. From NISQ applications like VQE to fault-tolerant quantum computing, unlock algorithms for research and application. Analyze performance, visualize circuits, and access tools for quantum chemistry and QAOA. Scale up with circuit cutting and explore pulse-level and qutrit representations.
+- <strong>*Master quantum algorithms*</strong>. From NISQ applications like VQE to fault-tolerant quantum computing, unlock algorithms for research and application. Analyze performance, visualize circuits, and access tools for [quantum chemistry](https://docs.pennylane.ai/en/stable/introduction/chemistry.html) and QAOA. Scale up with circuit cutting and explore pulse-level and qutrit representations.
 
-- *Quantum Datasets*. Access high-quality, pre-simulated datasets to decrease time-to-research and accelerate algorithm development. Easily [browse the datasets](https://pennylane.ai/datasets/) or contribute your own data.
+- <strong>*Quantum datasets*</strong>. Access high-quality, pre-simulated datasets to decrease time-to-research and accelerate algorithm development. Easily [browse the datasets](https://pennylane.ai/datasets/) or contribute your own data.
 
-- *Compilation and performance*. Capture hybrid quantum-classical workflows with just-in-time compilation, scaling from CPU to GPU. Decompose circuits into hardware-compatible gates and access high-performance simulators with fast quantum circuit differentiation. Easily install via pip, Conda, Spack, or Docker. See [Catalyst](https://github.com/pennylaneai/catalyst) for more details.
+- <strong>*Compilation and performance*</strong>. Capture hybrid quantum-classical workflows with just-in-time compilation, scaling from CPU to GPU. Decompose circuits into hardware-compatible gates and access high-performance simulators with fast quantum circuit differentiation. Easily install via pip, Conda, Spack, or Docker. See [Catalyst](https://github.com/pennylaneai/catalyst) for more details.
 
 ## Installation