https://community.wolfram.com RSS Feed for Wolfram Community showing any discussions tagged with Wolfram Language sorted by active. https://community.wolfram.com/groups/-/m/t/3781869 &[Wolfram Notebook][1] [1]: https://www.wolframcloud.com/obj/1a5be53f-c16e-4093-a015-de3af3a06c42 Housam Binous 2026-08-16T20:35:06Z https://community.wolfram.com/groups/-/m/t/3781258 Tooltips are very useful when analyzing time series, but DateListPlot does not show the Tooltips always. I tried PlotHighlighting and other options. When are the Tooltips shown and when are they not shown? Attached notebook shows actual data with Tooltips and without Tooltips. ![enter image description here][2] &[Wolfram Notebook][1] [1]: https://www.wolframcloud.com/obj/24f1d5c5-68d5-4a8b-aa1a-7d2dd137c2f9 [2]: https://community.wolfram.com//c/portal/getImageAttachment?filename=DateListPlotTooltips.jpg&userId=357084 Ricardo MARTINEZ-LAGUNES 2026-08-14T18:46:45Z https://community.wolfram.com/groups/-/m/t/2705871 Dear All, I am trying to find Integral[Cos[x]/x,{x,0,infinite}]. Integrate can not give a result since the expression is divergent. However, NIntegrate gives a result that I do not trust. Integrate[1/x Cos[x], {x, 0, \[Infinity]}] NIntegrate[1/x Cos[x], {x, 0, \[Infinity]}] Does anyone know if this integral can be taken? And how can we trust the result? Best wishes, İsa [1]: https://www.wolframcloud.com/obj/d711ecdc-9215-408a-b65a-5bf9cb0334ce Isa Comez 2022-11-18T14:30:23Z https://community.wolfram.com/groups/-/m/t/1992710 This is my QS: ![enter image description here][1] This is my Code: &[Wolfram Notebook][2] [1]: https://community.wolfram.com//c/portal/getImageAttachment?filename=Mixedpartialdifferentialequation.png&userId=1983492 [2]: https://www.wolframcloud.com/obj/470eec73-0424-4cbc-8ba9-c2613051e7c6 Yuhai Xiang 2020-06-01T19:19:58Z https://community.wolfram.com/groups/-/m/t/3781131 ![enter image description here][1] &[Wolfram Notebook][2] [1]: https://community.wolfram.com//c/portal/getImageAttachment?filename=2718hero-image.png&userId=1539902 [2]: https://www.wolframcloud.com/obj/3913da62-9056-46cb-9074-0c6d6b98978e Mohammad Bahrami 2026-08-14T16:57:12Z https://community.wolfram.com/groups/-/m/t/3680280 Built this over few weekends, an MCP server that connects AI agents (Claude, Codex etc) directly to your local Mathematica. It lets the agent run Wolfram Language code, manipulate frontend notebooks, export plots, and query Wolfram Alpha(82 tools total). You don't even need to know every Mathematica command, as the agent can look up functions and documentation on its own. Watch it in action: https://youtu.be/TjGSkvVyc1Y **Would love for people in this community to give it a try. Your feedback would help me keep improving it.** [](https://www.youtube.com/watch?v=TjGSkvVyc1Y) --- *An AI agent solving math, generating plots, and controlling a live Mathematica notebook. Errors are returned directly to the agent, no copy-pasting notebook output back into chat.* --- ## Documentation * **[GitHub Repository](https://github.com/AbhiRawat4841/mathematica-mcp)**: All files and documentations * **[Technical Reference](https://github.com/AbhiRawat4841/mathematica-mcp/blob/main/docs/technical-reference.md)**: Architecture, tools, and configuration * **[Security Model](https://github.com/AbhiRawat4841/mathematica-mcp/blob/main/SECURITY.md)**: Threat model, permissions, and vulnerability reporting * **[Benchmarks](https://github.com/AbhiRawat4841/mathematica-mcp/blob/main/docs/benchmarks.md)**: Performance data and reproduction steps * **[Contributing](https://github.com/AbhiRawat4841/mathematica-mcp/blob/main/CONTRIBUTING.md)**: Development setup, testing, and PR process * **[Changelog](https://github.com/AbhiRawat4841/mathematica-mcp/blob/main/CHANGELOG.md)**: Version history * **[Examples](https://github.com/AbhiRawat4841/mathematica-mcp/tree/main/docs/examples)**: Polished agent session walkthroughs ## Why This Exists LLMs can write Mathematica code, but they can't run it, verify it, or interact with live notebooks. This MCP server bridges that gap: - **Live notebook control**: create, edit, evaluate, and screenshot Mathematica notebooks directly from your AI agent - **Symbolic + numeric + visual in one MCP**: ~82 tools covering algebra, calculus, plotting, data import/export, Wolfram Alpha, and interactive UIs - **Agent-optimized**: compact response shaping, session state tools, and computation journaling designed for how LLM agents actually work - **Error-aware execution**: Mathematica errors and warnings are returned directly to the agent, so it can debug without you manually copying notebook output back into chat - **Local and private**: core execution runs on your machine — optional tools like `wolfram_alpha` and repository search contact Wolfram's cloud services when invoked > Ask your agent for a derivation, a 3D plot, a notebook edit, or a verification step, and it can actually do it. --- ## Who This Is For ![enter image description here][2] --- ## What You Can Ask For **"Integrate x^2 sin(x) from 0 to pi, then verify the result."** ```text execute_code("Integrate[x^2 Sin[x], {x, 0, Pi}]") => -4 + Pi^2 verify_derivation(steps=["Integrate[...", "-4 + Pi^2"]) => All steps valid ``` **"Plot the sombrero function in a new notebook."** ```text create_notebook(title="Sombrero") execute_code("Plot3D[Sinc[Sqrt[x^2+y^2]], {x,-4,4}, {y,-4,4}]", style="notebook") => [3D surface plot rendered in live notebook] ``` **"Interactive: slider for Sin[n x]"** ```text execute_code("Manipulate[Plot[Sin[n x],{x,0,2Pi}],{n,1,10}]", style="interactive") => [Live slider UI in Mathematica frontend] ``` Beyond these: **data import/export** (hundreds of formats), **Wolfram Alpha queries**, **notebook reading/analysis**, **symbolic debugging**, and more. See the [Technical Reference](docs/technical-reference.md) for the full tool list. --- ## How It Compares ![enter image description here][3] \*Core computation runs locally. Optional tools (`wolfram_alpha`, repository search) contact Wolfram cloud services when invoked. --- ## Quick Start From install to first working notebook plot in under 2 minutes. ### Prerequisites 1- **Mathematica 14.0+** with `wolframscript` in your PATH - [Download Mathematica](https://www.wolfram.com/mathematica/) - macOS: Add to `~/.zshrc`: `export PATH="/Applications/Mathematica.app/Contents/MacOS:$PATH"` 2- **uv package manager** curl -LsSf https://astral.sh/uv/install.sh | sh ### One-Command Setup ```bash # For Claude Desktop uvx mathematica-mcp-full setup claude-desktop # For Cursor uvx mathematica-mcp-full setup cursor # For VS Code (requires GitHub Copilot Chat extension) uvx mathematica-mcp-full setup vscode # For OpenAI Codex CLI uvx mathematica-mcp-full setup codex # For Google Gemini CLI uvx mathematica-mcp-full setup gemini # For Claude Code CLI uvx mathematica-mcp-full setup claude-code # Optional: select a tool profile (default is "full") uvx mathematica-mcp-full setup claude-desktop --profile notebook ``` Then restart Mathematica and your editor. Done! ####VS Code: Alternative setup via Command Palette > **Prerequisite:** [GitHub Copilot Chat](https://marketplace.visualstudio.com/items?itemName=GitHub.copilot-chat) extension must be installed - MCP support is built into Copilot. 1. Press `Cmd+Shift+P` (Mac) / `Ctrl+Shift+P` (Windows) 2. Type "MCP" -> Select **"MCP: Add Server"** 3. Choose **"Command (stdio)"**: *not "pip"* 4. Enter command: `uvx` 5. Enter args: `mathematica-mcp-full` 6. Name it: `mathematica` 7. Choose scope: Workspace or User ####Alternative: Interactive Installer ```bash bash <(curl -sSL https://raw.githubusercontent.com/AbhiRawat4841/mathematica-mcp/main/install.sh) ``` ### Verify Installation ```bash uvx mathematica-mcp-full doctor ``` > **Tip:** If you encounter errors after updating, clear the cache: > ```bash > uv cache clean mathematica-mcp-full && uvx mathematica-mcp-full setup <client> > ``` --- ## Execution Styles Control where results appear with natural language or the `style` parameter: ![enter image description here][4] If you don't include a keyword, the default depends on your [tool profile](#tool-profiles). --- ## Tool Profiles Choose how many tools to expose: ![enter image description here][5] Pass `--profile` during setup or set `MATHEMATICA_PROFILE` env var. --- ## Built for Agent Workflows The server is designed for how LLM agents actually work: long conversations with context limits, intermittent failures, and token budgets: ![enter image description here][6] Notebook execution is strict about the requested target: if notebook transport fails, the server returns a notebook error instead of silently rerunning the work through CLI fallback. ### Routing Intelligence (opt-in) For power users, the server can learn from transport outcomes and adapt: ```bash # Observe mode: collect stats, no behavior change export MATHEMATICA_ROUTING_MEMORY=observe # Advise mode: + routing hints + enables adaptive routing export MATHEMATICA_ROUTING_MEMORY=advise export MATHEMATICA_ROUTING_ACTION=compute_cli_skip # optional: skip failing transport ``` The adaptive routing circuit-breaker automatically skips persistently failing compute CLI transport with half-open probe recovery. See the [Technical Reference](docs/technical-reference.md#intelligent-routing--observability) for details. > **Privacy:** Routing memory stores only aggregate counters; the in-memory journal stores short code/output previews (not persisted). Notebook extraction results are cached to `~/.cache/mathematica-mcp/notebooks/` with mtime-based invalidation; delete the directory to clear the cache. --- ## Manual Installation For full details, troubleshooting, and advanced configuration, see the **[Installation Guide](docs/installation.md)**. ####Quick manual setup 1. **Clone & Install**: git clone https://github.com/AbhiRawat4841/mathematica-mcp.git cd mathematica-mcp uv sync 2. **Install Mathematica Addon**: wolframscript -file addon/install.wl *Restart Mathematica after this step.* 3. **Configure your editor**: add the MCP server to your client's config file. See the **[Installation Guide](docs/installation.md#step-4-configure-your-editor)** for Claude Desktop, Cursor, VS Code, and other client configs. --- ## License MIT License [1]: https://github.com/AbhiRawat4841/mathematica-mcp [2]: https://community.wolfram.com//c/portal/getImageAttachment?filename=Table1.jpg&userId=20103 [3]: https://community.wolfram.com//c/portal/getImageAttachment?filename=Table2.jpg&userId=20103 [4]: https://community.wolfram.com//c/portal/getImageAttachment?filename=Table3.jpg&userId=20103 [5]: https://community.wolfram.com//c/portal/getImageAttachment?filename=Table4.jpg&userId=20103 [6]: https://community.wolfram.com//c/portal/getImageAttachment?filename=Table5.jpg&userId=20103 Abhishek Singh Rawat 2026-04-10T00:05:40Z https://community.wolfram.com/groups/-/m/t/3780545 ![Analytical dynamics with Lagrange and Hamilton][1] &[Wolfram Notebook][2] [1]: https://community.wolfram.com//c/portal/getImageAttachment?filename=3675hero.png&userId=20103 [2]: https://www.wolframcloud.com/obj/046a414f-f3af-4e0e-9d20-7a1e47c11739 Akram Masoud 2026-08-13T23:11:11Z https://community.wolfram.com/groups/-/m/t/3779095 Parallel instances read a global but do not set a global? &[Wolfram Notebook][1] [1]: https://www.wolframcloud.com/obj/16b31aaa-f36c-4e26-a8d6-272b95854c7f David Golber 2026-08-11T15:42:12Z https://community.wolfram.com/groups/-/m/t/2137370 Suppose I have the following Dataset: ![enter image description here][1] I want to use ListPlot to produce a plot of v (voltage) vs. t (time). Seems quite simple and straightforward, but I didn't find an answer on the net. I was thinking about doing ListPlot[Thread[{mydata[All, "t"], mydata[All, "v"]}]] but `mydata[All, "t"]` gives an error: Failure[Dataset,Association["MessageTemplate" :> MessageName[Dataset, "partnotapplicable"],"MessageParameters" -> Association["Type" -> TypeSystem`Vector[TypeSystem`AnyType, 2], "Part" -> "t","Symbol" -> Part]]] I wouldn't be surprised to learn that there is a short way to do that, without the use of `Thread`. [1]: https://community.wolfram.com//c/portal/getImageAttachment?filename=9170csv.PNG&userId=1344988 Ehud Behar 2020-12-14T10:06:23Z https://community.wolfram.com/groups/-/m/t/3779221 &[Wolfram Notebook][1] [1]: https://www.wolframcloud.com/obj/647ded57-7011-451f-a59b-e75657fdc8d2 Housam Binous 2026-08-11T12:07:47Z https://community.wolfram.com/groups/-/m/t/3778637 This is a restatement of [this post][1], since it is difficult to read and [this post][2] since the latter might later be closed. I don't know where else to share. **Motivation:** Consider the function $\mathcal{G}:\mathbb{R}\to\mathbb{R}$, > (**Example of** $\mathcal{G}$) Let $(q_t)_{t\in\mathbb{N}}$ be a [numbering][3] of the rational numbers and $k_t=2^{2^t}$, and define functions $s_t$ as follows: > > If $s_0=0$ everywhere and: $$\small{ s_{t+1}(x)=\begin{cases} q_{t/2} & x\in\bigcup_{j\in\{1,\cdots,t\}}(q_j-1/k_t,q_j+1/k_t), \, t \text{ is even}\\ k_t^2 & x \in\bigcup_{j\in\{1,\cdots,t\}}(q_j-1/k_t,q_j+1/k_t), \, t \text{ is odd}\\ s_t(x) & \text{otherwise} \end{cases}}$$ each $s_{t+1}$ agrees with $s_t$ at all real numbers except a set of measure $<1/2^t$ for big $t$, so one could consider $\mathcal{G}$ the pointwise limit of the functions $s_t$, which is defined everywhere except measure $0$ (in those bad points just define $\mathcal{G}=0$). Here is the partial code of the example using Mathematica: Clear["Global`*"] enumerateRationals[n_Integer?Positive] := Module[{posRationals, fullList},(*Generate enough positive rationals using the Calkin- Wilf step*) posRationals = NestList[1/(2 Floor[#] - # + 1) &, 1, Ceiling[n/2]]; (*Interleave:0,q1,-q1,q2,-q2...*) fullList = Riffle[posRationals, -posRationals]; Prepend[fullList, 0][[1 ;; n]]]; enumerateRationals[0] = {}; q[t_] := q[t] = enumerateRationals[t][[t]] (*Takes the t-value in an enumeration*) k[t_] := k[t] = 2^(2^t) s[0, _] = 0; s[t_Integer, x_] := s[t, x] = Piecewise[{{q[(t - 1)/2], EvenQ[t - 1] && 0 <= Min[Abs[x - enumerateRationals[t - 1]]] < 1/k[t - 1]}, {k[ t - 1]^2, OddQ[t - 1] && 0 <= Min[Abs[x - enumerateRationals[t - 1]]] < 1/k[t - 1]}}, s[t - 1, x]] FullSimplify[PiecewiseExpand[s[5, x]]] (*Example of s[t,x]*) (I want to compute `s[t,x]` as `t->Infinity` to get $\mathcal{G}(x)$ or `bigG[x]`.) In the usual sense, the mean of $\mathcal{G}$ w.r.t. the Lebesgue measure over a family of bounded and finite measure sets converging to $\mathrm{dom}(\mathcal{G})=\mathbb{R}$ is always undefined, since $\mathcal{G}$ satisfies two properties: 1. The restriction of $\mathcal{G}$ to any interval has infinite area both above and below $y=0$. 2. For all $a<b$ and $c<d$ real numbers, $\{x\in (a,b):\mathcal{G}(x) \in (c,d)\}$ is a set with positive Lebesgue measure. Furthermore, the mean w.r.t. the Hausdorff measure in its dimension of a family of bounded functions (with different bounded domains of finite measure) converging to $\mathcal{G}$ is defined but has different values depending on the family of bounded functions chosen. Hence, the former mean is non-unique. **Question:** In my concept paper (see the following summary and attatchments), assuming $\mathbf{R}$ is the origin and $E=1/2$, what is the *average* of the example of $\mathcal{G}$ using Mathematica? Is the "average value" non-zero and finite? If not, explain why? > Every reference in the next section refers to the Sections, Definitions, and pages of the concept paper. ## Summary of The Concept Paper## My attempt to average of $\mathcal{G}(x)$ on $\small{(-\infty,+\infty)}$ is defined w.r.t. to four definitions: - The [reference point][6] $\mathbf{R}\in\mathbb{R}^{2}$: > For every *chosen* reference point, there should be a unique, "satisfying" (i.e., see the section "**Modeling Question Summary**" at the bottom), and either: > > 1. a finite mean of $\mathcal{G}$ > 2. if not a finite mean of $\mathcal{G}$, then an infinite mean > 3. if not a finite or infinite mean, then an undefined mean of $\mathcal{G}$. - The "measure" (Definitions 20-22 (pg. 20-25) of a family of each bounded function’s graph, where $\{G_r^{\star}:r\in\mathbb{R}^{+}\}=\{\mathrm{graph}(f_r^{\star}):r\in\mathbb{R}^{+}\}$ and $\{f_r^{\star}:r\in\mathbb{R}^{+}\}$ is a family of bounded functions with different bounded domains of finite measure converging to $\mathcal{G}$): > The preliminary step to defining the "measure" of a family of each bounded function's graph (Definition 20, pg. 20-22) is to partition each of their graphs into equal measure sets which take a sample point from each partition, pathways of line segments between sample points, lengths of line segments in each pathway, removed lengths which are outliers, remaining lengths which are converted into a probability distribution, the entropy of the distribution, and the maximum entropy w.r.t all pathways. > > ----------------- > > 'The "measure" (Definition 22, pg. 23-25) involves the supremum of the sample size (i.e., when applying the preliminary step to each bounded function's graph in a chosen family) such that the entropy in the preliminary step is less than or equal to the entropy (i.e., when applying the preliminary step to each bounded function's graph in a "non-equivalent" family [Definition 18-19, pg. 19-20]), then dividing the former by the following sample size (i.e., when applying the preliminary step to each bounded function's graph in the "non-equivelant" family) and taking its "supremum" and "infimum" w.r.t. to all possible partitions and samples. (The "supremum" and "infimum" should be equal.) To better understand the definitions, consider the following examples (Section A.7.1-A.7.3, pg. 179-197). - The expected rate of expansion: > The expected rate of expansion is an arbitrary fixed constant and is > written as the function $E:\mathcal{A}(A)\to\mathbb{R}$ (i.e., > $\mathcal{A}(A):=\mathbb{R}^{+}$ is the chosen index set of a family of functions or > sets). - The actual rate of expansion (Definition 23, pg. 25-26): > The actual rate of expansion of a family of each bounded function's > graph is the "derivative" of a function of the "average" $2$-dimensional Euclidean > distance between every point in each bounded function's graph and the > reference point $\mathbf{R}\in\mathbb{R}^{2}$ ------- ### Modeling Question Summary: ### > Combining "the measure" and the actual rate of expansion, we get a general notion of the choice function in the modeling question (Section 3.1, pg. 27-30). The choice function should pick "equivelant" families (Definition 15-17, pg. 17-18) of bounded functions converging to $\mathcal{G}$ which satisfy all the criteria in the modeling question, such that: > - the "measure" (Definition 20-22, pg. 20-25) of each chosen family of each bounded function's graph increases at a rate linear or superlinear (Definition 22, pg. 23-25) to that of each "non-equivelant" family (Definition 18-19, pg. 19-20) of each bounded function's graph (Section 3.1 criterion 2) - the absolute difference between the $y$-coordinate of the reference point $\mathbf{R}\in\mathbb{R}^{2}$ and the mean of each chosen family of bounded functions converging to $\mathcal{G}$ is minimized (Definition 13 [pg. 13-14], Section 3.1 criterion 4) - the absolute difference between the expected rate of expansion and the actual rate of expansion of each chosen family of each bounded function's graph is minimized (Definition 23 [pg. 25-26], Section 3.1 criterion 4), > so that it's more likely the choice function, which answers the modeling question, chooses the desired families. Hence, we take the mean of the chosen "equivelant" (Definition 15-17, pg. 17-18) families as the new mean (i.e., the "equivelant" families should have the same mean). [1]: https://community.wolfram.com/groups/-/m/t/3769559?p_p_auth=EIl3sQDy [2]: https://scicomp.stackexchange.com/questions/45512/can-we-average-pathological-function-mathcalg-mathbbr-to-mathbbr-in-a [3]: https://en.wikipedia.org/wiki/Calkin%E2%80%93Wilf_tree [4]: https://mathematica.stackexchange.com/a/319780/34171 [5]: https://www.researchgate.net/publication/410022187_Reformatted_Averaging_an_Explicit_Non-Lebesgue_Integrable_and_Unbounded_Function_That_Is_Defined_Without_The_Axiom_of_Choice [6]: https://en.wikipedia.org/wiki/Frame_of_reference Bharath Krishnan 2026-08-11T00:50:32Z https://community.wolfram.com/groups/-/m/t/3778625 &[Wolfram Notebook][1] [1]: https://www.wolframcloud.com/obj/e3780e27-7c98-4efc-9494-86f49cddb5ab Housam Binous 2026-08-10T23:44:18Z https://community.wolfram.com/groups/-/m/t/3778307 &[Wolfram Notebook][1] [1]: https://www.wolframcloud.com/obj/691e48da-b2e1-4830-81fa-a3e76d150693 Housam Binous 2026-08-10T15:42:23Z https://community.wolfram.com/groups/-/m/t/3776120 &[Wolfram Notebook][1] [1]: https://www.wolframcloud.com/obj/67574a39-6fe3-4b96-a0e0-e2fcc394ee18 Housam Binous 2026-08-08T13:48:19Z https://community.wolfram.com/groups/-/m/t/3631132 Hello everyone, I am developing a model of spacetime that shares some fundamental concepts with the Wolfram Physics Project but introduces a specific focus on testability and quantum noise signatures. In my theory, spacetime is represented as a finite directed quantum graph. The core idea is that the connectivity of the graph isn't just an abstract representation but directly dictates the physical observables we see in quantum systems. Key features of the model: Discrete Topology: Nodes represent Planck-scale events, and directed edges represent causal relationships. Emergent Physics: I have derived that the Einstein field equations and Maxwell's equations emerge as a low-energy limit of these graph dynamics. Experimental Predictions: Most importantly, the model predicts specific spectral signatures in the decoherence noise of current NISQ-era quantum processors and anomalies in high-energy particle scattering. Iam looking for collaborators who are interested in: Visualizing the graph dynamics using the Wolfram Language. Simulating the noise patterns to compare them with existing data from IBM or Google quantum hardware. I believe that by identifying the right "rewrite rules" for this directed graph, we can bridge the gap between discrete spacetime models and experimental verification. Looking forward to your feedback and potential collaboration! Sergej Materov 2026-01-30T11:52:49Z https://community.wolfram.com/groups/-/m/t/3775105 &[3][1] [1]: https://www.wolframcloud.com/obj/8c0f3da8-ac8c-4ae3-80f3-6f03079a146c Housam Binous 2026-08-06T08:27:07Z https://community.wolfram.com/groups/-/m/t/3773927 Complaint: The examples in the Mathematica Help are needlessly complicated, and in fact hinder the process of informing the user. Here's an example: The first example of the use of Parallelize, in the definition of the Parallelize operation, is (1) Parallelize[Map[Composition[Framed,FactorInteger],{1,11,111,1111,11111,111111}]] This is more or less (2) Parallelize[{FactorInteger[1], FactorInteger[11], FactorInteger[111], FactorInteger[1111], FactorInteger[11111], FactorInteger[111111]}] Which takes about 50% more characters, but only two operators (Parallelize and FactorInteger) instead of five (Parallelize, Map, Composition, Framed, FactorInteger). But, in fact, neither (1) or (2) tells the reader anything more about what Parallelize does, or how to use it, than (3) Parallelize[{1^2, 2^2, 3^2, 4^2, 5^2, 6^2}] (3) has no operators other than the one which the example is there to explain. And it has fewer characters than (1) or (2). Can anyone defend why (1) should be the example instead of (3). David Golber 2026-08-05T01:09:19Z https://community.wolfram.com/groups/-/m/t/2380163 I recently noticed that Mathematica uses MxNet as the backend for neural networks. It seems to have been integrated in 2015. The blog post listing the rationale is [here](https://www.oreilly.com/content/apache-mxnet-in-the-wolfram-language/). MxNet seems to have not gained the momentum to become popular, you can see the [trends](https://paperswithcode.com/trends) from "papers with code". Lack of popularity means framework may be slow to develop. For instance, this [question](https://mathematica.stackexchange.com/questions/256323/neural-network-automatic-differentiation-autograd) about using neural networks to fit ODEs from Joshua Schrier. It requires underlying framework to support higher order gradients. There's an [issue](https://github.com/apache/incubator-mxnet/issues/10002) to add support in MxNET but progress has stalled. Meanwhile PyTorch/TensorFlow/JAX support this feature. Yaroslav Bulatov 2021-10-06T00:49:07Z https://community.wolfram.com/groups/-/m/t/3143033 I have a general question that may have been addressed previously, albeit not directly. I utilize Mathematica to solve a set of non-linear equations and achieve successful results. However, the computation time is considerably long despite the minimal CPU and memory usage. Additionally, the computer I am using is a high-performance PC, yet the execution speed of this code resembles that of my laptop. Am I overlooking something? Why isn't Mathematica utilizing more resources? For instance, the CPU usage remains around 7% max. Nima Moini 2024-03-18T23:02:58Z https://community.wolfram.com/groups/-/m/t/3067055 Hi all, I've been using WL this year in physics. Each student has created a cloud folder called "Physics" to store their project notebooks. We just had a major project completed this week and we are about to go on Fall break. I had them all share their notebooks with me via email. I would rather have a shared folder in which they put their work. When you look at the properties of a folder in the cloud, you can see "permissions" which has a default setting of private. Is it possible to create a CloudObject that is a named folder, set Permissions to "Public" and then distribute the URL of that object to my students? If possible, is this the way people generally do this? John Martin 2023-11-17T20:24:51Z