Merge pull request #3 from neural-loop/linked-content

Linked content

Author: neural-loop

content/blog/northpole-ibm-neuromorphic-ai-hardware/index.md

@@ -7,11 +7,11 @@ date: 2023-12-26
 showTableOfContents: true
 author:
   - Fabrizio Ottati
-hardware_tags: ["truenorth-ibm"]
+hardware_tags: ["northpole-ibm","truenorth-ibm"]
 show_author_bios: true
 ---
 
-[NorthPole](https://research.ibm.com/blog/northpole-ibm-ai-chip) is the new shiny artificial intelligence (AI) accelerator developed by IBM.
+[NorthPole](/neuromorphic-computing/hardware/northpole-ibm) is the new shiny artificial intelligence (AI) accelerator developed by IBM.
 
 > NorthPole, an architecture and a programming model for neural inference, reimagines (Fig. 1) the interaction between compute and memory by embodying 10 interrelated, synergistic axioms that build on brain-inspired computing.
 

content/contributors/alexander-hadjiivanov/index.md

@@ -6,9 +6,5 @@ social: []
 draft: false
 ---
 Alex is currently a Research Fellow with the Advanced Concepts Team at the European Space Agency. His research focuses on homeostasis, perception and structural plasticity in classical and spiking neural networks. When he has time, he also works on <a href="https://gitlab.com/EuropeanSpaceAgency/pyrception">Pyrception, an easy way to interface various types of input data with neural networks</a>.
-<br><br>
-No single branch of AI can claim the crown of true intelligence on its own. Rather,
-developing AI worthy of the ''I'' would require a concerted effort to combine
-virtually all the branches - from perception through learning and cognition to
-reasoning and interaction. The most enticing aspect of neuromorphic computing
-is its potential to bring about this unification.
+
+No single branch of AI can claim the crown of true intelligence on its own. Rather, developing AI worthy of the ''I'' would require a concerted effort to combine virtually all the branches - from perception through learning and cognition to reasoning and interaction. The most enticing aspect of neuromorphic computing is its potential to bring about this unification.

content/contributors/alexander-henkes/index.md

@@ -5,20 +5,10 @@ image: "alexander-henkes.jpg"
 social: []
 draft: false
 ---
-Alexander Henkes received the B.Sc. (Mechanical Engineering) and M.Sc.
-(Mechanical Engineering) degrees from the University of Paderborn, Germany, in
-2015 and 2018, respectively. In 2022, he received his Ph.D. with honors from the
-Technical University of Braunschweig (TUBS), Germany, for his thesis ''Artificial
-Neural Networks in Continuum Micromechanics''.
+Alexander Henkes received the B.Sc. (Mechanical Engineering) and M.Sc. (Mechanical Engineering) degrees from the University of Paderborn, Germany, in 2015 and 2018, respectively. In 2022, he received his Ph.D. with honors from the Technical University of Braunschweig (TUBS), Germany, for his thesis ''Artificial Neural Networks in Continuum Micromechanics''.
 
-In 2022, he was elected as a junior member of the German Association of Applied
-Mathematics and Mechanics (GAMM) for his outstanding research in the field of
-artificial intelligence in continuum micromechanics. In 2023, he won the ETH Zürich
-Postdoctoral Fellowship and joined the Computational Mechanics group at ETH as
-a postdoc.
+In 2022, he was elected as a junior member of the German Association of Applied Mathematics and Mechanics (GAMM) for his outstanding research in the field of artificial intelligence in continuum micromechanics. In 2023, he won the ETH Zürich Postdoctoral Fellowship and joined the Computational Mechanics group at ETH as a postdoc.
 
-His current research focuses on spiking neural networks (SNN). Recently, he published
-a preprint on nonlinear history-dependent regression using SNN. This enables SNN
-to be used in the context of applied mathematics and computational engineering.
+His current research focuses on spiking neural networks (SNN). Recently, he published a preprint on nonlinear history-dependent regression using SNN. This enables SNN to be used in the context of applied mathematics and computational engineering.
 
-He is a contributor of [snnTorch](https://github.com/jeshraghian/snntorch).
+He is a contributor of [snnTorch](/neuromorphic-computing/software/snn-frameworks/snntorch/).

content/contributors/bernhard-vogginger/index.md

@@ -5,4 +5,4 @@ image: "" # To be replaced with "bernhard-vogginger.jpg" or similar
 social: []
 draft: false
 ---
-Bernhard Vogginger is a research associate at TU Dresden working on neuromorphic computing software and applications in the lab of Prof. Christian Mayr. He currently leads the software development for the SpiNNaker2 neuromorphic system and has co-authored the [Neuromorphic Intermediate Representation](https://github.com/neuromorphs/nir). Further research interests include radar processing and sustainability of AI and data centers.
+Bernhard Vogginger is a research associate at TU Dresden working on neuromorphic computing software and applications in the lab of Prof. Christian Mayr. He currently leads the software development for the [SpiNNaker2](/neuromorphic-computing/hardware/spinnaker-2-university-of-dresden/) neuromorphic system and has co-authored the [Neuromorphic Intermediate Representation (NIR)](/workshops/neuromorphic-intermediate-representation/). Further research interests include radar processing and sustainability of AI and data centers.

content/contributors/carlos-ortega-otero/index.md

@@ -7,6 +7,6 @@ draft: false
 ---
 Dr. Carlos Ortega-Otero is an Sr. Research Staff Member at IBM driven by a passion in Circuit Design, Neuromorphic Chip Architectures, Low-Power Circuits and Physical Design optimizations. He earned his Ph.D. from Cornell University under the guidance of Prof. Rajit Manohar.
 
-Throughout his career, he has worked in groundbreaking projects, including Ultra-Low Power Asynchronous Sensor Network nodes, Medical Implantable Wireless Sensors, The TrueNorth Brain-Inspired Chip, and the NorthPole Project. At IBM, Carlos works under the leadership of Dr. Dharmendra Modha in the Brain-Inspired Computing Group.
+Throughout his career, he has worked in groundbreaking projects, including Ultra-Low Power Asynchronous Sensor Network nodes, Medical Implantable Wireless Sensors, The [TrueNorth](/neuromorphic-computing/hardware/truenorth-ibm/) Brain-Inspired Chip, and the [NorthPole Project](/blog/northpole-ibm-neuromorphic-ai-hardware/). At IBM, Carlos works under the leadership of Dr. Dharmendra Modha in the Brain-Inspired Computing Group.
 
 He plays key roles in Architecture, Specification, Digital Implementation, Physical Design, Timing Signoff, and Manufacturing teams of the NorthPole Project. Carlos is proud to be part of the Brain-Inspired Computing Group at IBM that continues to shape the future of Integrated Circuits and AI.

content/contributors/catherine-schuman/index.md

@@ -5,15 +5,6 @@ image: "catherine-schuman.jpg"
 social: []
 draft: false
 ---
-Catherine (Katie) Schuman is an Assistant Professor in the Department
-of Electrical Engineering and Computer Science at the University of Tennessee
-(UT). She received her Ph.D. in Computer Science from UT in 2015, where she completed
-her dissertation on the use of evolutionary algorithms to train spiking neural
-networks for neuromorphic systems. Katie previously served as a research scientist
-at Oak Ridge National Laboratory, where her research focused on algorithms and
-applications of neuromorphic systems.
+Catherine (Katie) Schuman is an Assistant Professor in the Department of Electrical Engineering and Computer Science at the University of Tennessee (UT). She received her Ph.D. in Computer Science from UT in 2015, where she completed her dissertation on the use of evolutionary algorithms to train spiking neural networks for neuromorphic systems. Katie previously served as a research scientist at Oak Ridge National Laboratory, where her research focused on algorithms and applications of neuromorphic systems.
 
-
-Katie co-leads the TENNLab Neuromorphic Computing Research Group at UT. She has
-over 100 publications as well as seven patents in the field of neuromorphic computing.
-She received the Department of Energy Early Career Award in 2019.
+Katie co-leads the TENNLab Neuromorphic Computing Research Group at UT. She has over 100 publications as well as seven patents in the field of neuromorphic computing. She received the Department of Energy Early Career Award in 2019.

content/contributors/charlotte-frenkel/index.md

@@ -5,20 +5,13 @@ image: "charlotte-frenkel.jpg" # Assuming charlotte-frenkel.jpg is in this bundl
 social: [] # Add social links if available, e.g., { icon: "fa-brands fa-github", link: "https://github.com/ChFrenkel", title: "github" }
 draft: false
 ---
-Charlotte Frenkel is an Assistant Professor at the Microelectronics
-department of Delft University of Technology, Delft, The Netherlands.
+Charlotte Frenkel is an Assistant Professor at the Microelectronics department of Delft University of Technology, Delft, The Netherlands.
 
 Her research goals are:
 
-- to demonstrate a competitive advantage for neuromorphic computing devices compared
-to conventional neural network accelerators,
+- to demonstrate a competitive advantage for neuromorphic computing devices compared to conventional neural network accelerators,
+- to uncover a framework toward on-chip neuromorphic intelligence for adaptive edge computing.
 
-- to uncover a framework toward on-chip neuromorphic intelligence for adaptive
-edge computing.
+To achieve these goals, she is investigating both the bottom-up and the top-down design approaches, as well as their synergies.
 
-
-To achieve these goals, she is investigating both the bottom-up and the top-down
-design approaches, as well as their synergies.
-
-She is the designer of the [ODIN](https://github.com/ChFrenkel/ODIN) and [ReckOn](https://github.com/ChFrenkel/ReckOn)
-open-source online-learning digital neuromorphic processors.
+She is the designer of the [ODIN](/neuromorphic-computing/hardware/odin-frenkel/) and [ReckOn](/neuromorphic-computing/hardware/reckon-frenkel/) open-source online-learning digital neuromorphic processors.

content/contributors/fabrizio-ottati/index.md

@@ -15,4 +15,4 @@ Fabrizio Ottati completed his Ph.D. in the Department of Electronics and Communi
 
 His main interests are event-based cameras, digital hardware design and automation, deep learning and piedmontese red wine.
 
-He is the maintainer of two open source projects in the field of neuromorphic computing, [Tonic](https://tonic.readthedocs.io) and [Expelliarmus](https://expelliarmus.readthedocs.io).
+He is the maintainer of two open source projects in the field of neuromorphic computing, [Tonic](/neuromorphic-computing/software/data-tools/tonic/) and [Expelliarmus](/neuromorphic-computing/software/data-tools/expelliarmus/).

content/contributors/felix-bauer/index.md

@@ -8,4 +8,4 @@ social:
     title: "github"
 draft: false
 ---
-Felix Bauer is a neuromorphic engineer working on cutting-edge algorithms and chips at [SynSense](https://www.synsense.ai/). He co-authored the [Neuromorphic Intermediate Representation](https://github.com/neuromorphs/nir) and has published work on GPU-accelerated spiking neural networks via the [Sinabs](https://sinabs.readthedocs.io/) simulator, neuromorphic control and brain-machine interfaces.
+Felix Bauer is a neuromorphic engineer working on cutting-edge algorithms and chips at [SynSense](https://www.synsense.ai/). He co-authored the [Neuromorphic Intermediate Representation (NIR)](/workshops/neuromorphic-intermediate-representation/) and has published work on GPU-accelerated spiking neural networks via the [Sinabs](/neuromorphic-computing/software/snn-frameworks/sinabs/) simulator, neuromorphic control and brain-machine interfaces.

content/contributors/gregor-lenz/index.md

@@ -15,4 +15,4 @@ Gregor Lenz, Co-Founder and CTO at [Neurobus](https://neurobus.space), graduated
 
 His main interests are event cameras that are inspired by the human retina and spiking neural networks that mimic human brain in an effort to teach machines to compute a bit more like humans do. At the very least there are some power efficiency gains to be made, but hopefully more! Also he loves to build open source software for spike-based machine learning.
 
-He is the maintainer of two open source projects in the field of neuromorphic computing, [Tonic](https://github.com/neuromorphs/tonic) and [expelliarmus](https://github.com/open-neuromorphic/expelliarmus).
+He is the maintainer of two open source projects in the field of neuromorphic computing, [Tonic](/neuromorphic-computing/software/data-tools/tonic/) and [expelliarmus](/neuromorphic-computing/software/data-tools/expelliarmus/).