Ceacer

Per Inside EVs, Cybertruck owners are now allowed by Tesla to trade in their cars for the first time since they hit the market – but they’ll incur a heavy hit in the process. CarGurus recently showed depreciation rates of up to 45%. Meanwhile, Business Insider talked this past week with two owners who shared firsthand what value Tesla has assigned their Cybertruck. One owner, who bought a $100,000 AWD 2024 model and accumulated 19,623 miles, received a quote for $63,100 (a 37% depreciation); the other purchased a top-of-the-line $127,000 Cyberbeast last September was shown a quote for $78,200, which would amount to a 38% loss after eight months. Tesla initially banned owners from reselling the vehicle – a policy typically used to prevent scalping of high-demand vehicles and to maintain brand control. In Tesla’s case, it may also have delayed a wave of trade-ins or resales from owners facing a backlash owing to Elon Musk’s high profile in the Trump administration or frustrated with ongoing quality control issues, which have included runaway gas pedals and falling trim pieces. Worth noting: trade-in figures are typically lower than private-party sales, and EVs as a category depreciate fast. According to Wired, some brands can lose up to 50% in year one.

Artificial intelligence is a deep and convoluted world. The scientists who work in this field often rely on jargon and lingo to explain what they’re working on. As a result, we frequently have to use those technical terms in our coverage of the artificial intelligence industry. That’s why we thought it would be helpful to put together a glossary with definitions of some of the most important words and phrases that we use in our articles. We will regularly update this glossary to add new entries as researchers continually uncover novel methods to push the frontier of artificial intelligence while identifying emerging safety risks. AGI Artificial general intelligence, or AGI, is a nebulous term. But it generally refers to AI that’s more capable than the average human at many, if not most, tasks. OpenAI CEO Sam Altman recently described AGI as the “equivalent of a median human that you could hire as a co-worker.” Meanwhile, OpenAI’s charter defines AGI as “highly autonomous systems that outperform humans at most economically valuable work.” Google DeepMind’s understanding differs slightly from these two definitions; the lab views AGI as “AI that’s at least as capable as humans at most cognitive tasks.” Confused? Not to worry — so are experts at the forefront of AI research. AI agent An AI agent refers to a tool that uses AI technologies to perform a series of tasks on your behalf — beyond what a more basic AI chatbot could do — such as filing expenses, booking tickets or a table at a restaurant, or even writing and maintaining code. However, as we’ve explained before, there are lots of moving pieces in this emergent space, so “AI agent” might mean different things to different people. Infrastructure is also still being built out to deliver on its envisaged capabilities. But the basic concept implies an autonomous system that may draw on multiple AI systems to carry out multistep tasks. Chain of thought Given a simple question, a human brain can answer without even thinking too much about it — things like “which animal is taller, a giraffe or a cat?” But in many cases, you often need a pen and paper to come up with the right answer because there are intermediary steps. For instance, if a farmer has chickens and cows, and together they have 40 heads and 120 legs, you might need to write down a simple equation to come up with the answer (20 chickens and 20 cows). In an AI context, chain-of-thought reasoning for large language models means breaking down a problem into smaller, intermediate steps to improve the quality of the end result. It usually takes longer to get an answer, but the answer is more likely to be correct, especially in a logic or coding context. Reasoning models are developed from traditional large language models and optimized for chain-of-thought thinking thanks to reinforcement learning. (See: Large language model) Techcrunch event Join us at TechCrunch Sessions: AI Secure your spot for our leading AI industry event with speakers from OpenAI, Anthropic, and Cohere. For a limited time, tickets are just $292 for an entire day of expert talks, workshops, and potent networking. Exhibit at TechCrunch Sessions: AI Secure your spot at TC Sessions: AI and show 1,200+ decision-makers what you’ve built — without the big spend. Available through May 9 or while tables last. Berkeley, CA | June 5 REGISTER NOW Deep learning A subset of self-improving machine learning in which AI algorithms are designed with a multi-layered, artificial neural network (ANN) structure. This allows them to make more complex correlations compared to simpler machine learning-based systems, such as linear models or decision trees. The structure of deep learning algorithms draws inspiration from the interconnected pathways of neurons in the human brain. Deep learning AI models are able to identify important characteristics in data themselves, rather than requiring human engineers to define these features. The structure also supports algorithms that can learn from errors and, through a process of repetition and adjustment, improve their own outputs. However, deep learning systems require a lot of data points to yield good results (millions or more). They also typically take longer to train compared to simpler machine learning algorithms — so development costs tend to be higher. (See: Neural network) Diffusion Diffusion is the tech at the heart of many art-, music-, and text-generating AI models. Inspired by physics, diffusion systems slowly “destroy” the structure of data — e.g. photos, songs, and so on — by adding noise until there’s nothing left. In physics, diffusion is spontaneous and irreversible — sugar diffused in coffee can’t be restored to cube form. But diffusion systems in AI aim to learn a sort of “reverse diffusion” process to restore the destroyed data, gaining the ability to recover the data from noise. Distillation Distillation is a technique used to extract knowledge from a large AI model with a ‘teacher-student’ model. Developers send requests to a teacher model and record the outputs. Answers are sometimes compared with a dataset to see how accurate they are. These outputs are then used to train the student model, which is trained to approximate the teacher’s behavior. Distillation can be used to create a smaller, more efficient model based on a larger model with a minimal distillation loss. This is likely how OpenAI developed GPT-4 Turbo, a faster version of GPT-4. While all AI companies use distillation internally, it may have also been used by some AI companies to catch up with frontier models. Distillation from a competitor usually violates the terms of service of AI API and chat assistants. Fine-tuning This refers to the further training of an AI model to optimize performance for a more specific task or area than was previously a focal point of its training — typically by feeding in new, specialized (i.e., task-oriented) data. Many AI startups are taking large language models as a starting point to build a commercial product but are vying to amp up utility for a target sector or task by supplementing earlier training cycles with fine-tuning based on their own domain-specific knowledge and expertise. (See: Large language model [LLM]) GAN A GAN, or Generative Adversarial Network, is a type of machine learning framework that underpins some important developments in generative AI when it comes to producing realistic data – including (but not only) deepfake tools. GANs involve the use of a pair of neural networks, one of which draws on its training data to generate an output that is passed to the other model to evaluate. This second, discriminator model thus plays the role of a classifier on the generator’s output – enabling it to improve over time. The GAN structure is set up as a competition (hence “adversarial”) – with the two models essentially programmed to try to outdo each other: the generator is trying to get its output past the discriminator, while the discriminator is working to spot artificially generated data. This structured contest can optimize AI outputs to be more realistic without the need for additional human intervention. Though GANs work best for narrower applications (such as producing realistic photos or videos), rather than general purpose AI. Hallucination Hallucination is the AI industry’s preferred term for AI models making stuff up – literally generating information that is incorrect. Obviously, it’s a huge problem for AI quality. Hallucinations produce GenAI outputs that can be misleading and could even lead to real-life risks — with potentially dangerous consequences (think of a health query that returns harmful medical advice). This is why most GenAI tools’ small print now warns users to verify AI-generated answers, even though such disclaimers are usually far less prominent than the information the tools dispense at the touch of a button. The problem of AIs fabricating information is thought to arise as a consequence of gaps in training data. For general purpose GenAI especially — also sometimes known as foundation models — this looks difficult to resolve. There is simply not enough data in existence to train AI models to comprehensively resolve all the questions we could possibly ask. TL;DR: we haven’t invented God (yet). Hallucinations are contributing to a push towards increasingly specialized and/or vertical AI models — i.e. domain-specific AIs that require narrower expertise – as a way to reduce the likelihood of knowledge gaps and shrink disinformation risks. Inference Inference is the process of running an AI model. It’s setting a model loose to make predictions or draw conclusions from previously-seen data. To be clear, inference can’t happen without training; a model must learn patterns in a set of data before it can effectively extrapolate from this training data. Many types of hardware can perform inference, ranging from smartphone processors to beefy GPUs to custom-designed AI accelerators. But not all of them can run models equally well. Very large models would take ages to make predictions on, say, a laptop versus a cloud server with high-end AI chips. [See: Training] Large language model (LLM) Large language models, or LLMs, are the AI models used by popular AI assistants, such as ChatGPT, Claude, Google’s Gemini, Meta’s AI Llama, Microsoft Copilot, or Mistral’s Le Chat. When you chat with an AI assistant, you interact with a large language model that processes your request directly or with the help of different available tools, such as web browsing or code interpreters. AI assistants and LLMs can have different names. For instance, GPT is OpenAI’s large language model and ChatGPT is the AI assistant product. LLMs are deep neural networks made of billions of numerical parameters (or weights, see below) that learn the relationships between words and phrases and create a representation of language, a sort of multidimensional map of words. These models are created from encoding the patterns they find in billions of books, articles, and transcripts. When you prompt an LLM, the model generates the most likely pattern that fits the prompt. It then evaluates the most probable next word after the last one based on what was said before. Repeat, repeat, and repeat. (See: Neural network) Neural network A neural network refers to the multi-layered algorithmic structure that underpins deep learning — and, more broadly, the whole boom in generative AI tools following the emergence of large language models. Although the idea of taking inspiration from the densely interconnected pathways of the human brain as a design structure for data processing algorithms dates all the way back to the 1940s, it was the much more recent rise of graphical processing hardware (GPUs) — via the video game industry — that really unlocked the power of this theory. These chips proved well suited to training algorithms with many more layers than was possible in earlier epochs — enabling neural network-based AI systems to achieve far better performance across many domains, including voice recognition, autonomous navigation, and drug discovery. (See: Large language model [LLM]) Training Developing machine learning AIs involves a process known as training. In simple terms, this refers to data being fed in in order that the model can learn from patterns and generate useful outputs. Things can get a bit philosophical at this point in the AI stack — since, pre-training, the mathematical structure that’s used as the starting point for developing a learning system is just a bunch of layers and random numbers. It’s only through training that the AI model really takes shape. Essentially, it’s the process of the system responding to characteristics in the data that enables it to adapt outputs towards a sought-for goal — whether that’s identifying images of cats or producing a haiku on demand. It’s important to note that not all AI requires training. Rules-based AIs that are programmed to follow manually predefined instructions — for example, such as linear chatbots — don’t need to undergo training. However, such AI systems are likely to be more constrained than (well-trained) self-learning systems. Still, training can be expensive because it requires lots of inputs — and, typically, the volumes of inputs required for such models have been trending upwards. Hybrid approaches can sometimes be used to shortcut model development and help manage costs. Such as doing data-driven fine-tuning of a rules-based AI — meaning development requires less data, compute, energy, and algorithmic complexity than if the developer had started building from scratch. [See: Inference] Transfer learning A technique where a previously trained AI model is used as the starting point for developing a new model for a different but typically related task – allowing knowledge gained in previous training cycles to be reapplied. Transfer learning can drive efficiency savings by shortcutting model development. It can also be useful when data for the task that the model is being developed for is somewhat limited. But it’s important to note that the approach has limitations. Models that rely on transfer learning to gain generalized capabilities will likely require training on additional data in order to perform well in their domain of focus (See: Fine tuning) Weights Weights are core to AI training, as they determine how much importance (or weight) is given to different features (or input variables) in the data used for training the system — thereby shaping the AI model’s output. Put another way, weights are numerical parameters that define what’s most salient in a dataset for the given training task. They achieve their function by applying multiplication to inputs. Model training typically begins with weights that are randomly assigned, but as the process unfolds, the weights adjust as the model seeks to arrive at an output that more closely matches the target. For example, an AI model for predicting housing prices that’s trained on historical real estate data for a target location could include weights for features such as the number of bedrooms and bathrooms, whether a property is detached or semi-detached, whether it has parking, a garage, and so on. Ultimately, the weights the model attaches to each of these inputs reflect how much they influence the value of a property, based on the given dataset.

Teddy Warner, 19, has always been interested in robotics. His family was in the industry, and he says he “grew up” working in a machinist shop while in high school. Now Warner is building a robotics company of his own, Intempus, that looks to make robots a bit more human. Intempus is building tech to retrofit existing robots with human-like emotional expressions to help humans better interact with these machines and better predict their movements. Giving these robots human-like reactions will also produce data that can be used to better train AI models. These robots will show expression through kinetic movements, Warner told TechCrunch. “Humans derive a lot of our subconscious signals, not from face, not from semantics, but solely from the movement of your arms and your torso,” Warner said. “This extends to dogs and cats and other animals that aren’t humans.” Image Credits:Teddy Warner Warner said he got the idea for Intempus while he was working at AI research lab Midjourney. He said Midjourney, like many other AI research labs, was working on world AI models, or AI models that understand and make decisions based on the dynamics of the real world and spatial properties, as opposed to just cause and effect. But it will be really hard for these models to achieve this spatial reasoning, Warner realized, because a lot of the data the models were being trained on came from robots that didn’t have this spatial reasoning, either. “Robots currently go from A to C, that is observation to action, whereas humans, and all living things, have this intermediary B step that we call physiological state,” Warner said. “Robots don’t have physiological state. They don’t have fun, they don’t have stress. If we want robots to understand the world like a human can, and be able to communicate with humans in a way that is innate to us, that is less uncanny, more predictable, we have to give them this B step.” Techcrunch event Join us at TechCrunch Sessions: AI Secure your spot for our leading AI industry event with speakers from OpenAI, Anthropic, and Cohere. For a limited time, tickets are just $292 for an entire day of expert talks, workshops, and potent networking. Exhibit at TechCrunch Sessions: AI Secure your spot at TC Sessions: AI and show 1,200+ decision-makers what you’ve built — without the big spend. Available through May 9 or while tables last. Berkeley, CA | June 5 REGISTER NOW Warner took that idea and started to research. He started with fMRI data, which measures brain activity by detecting changes in blood flow and oxygen, but it didn’t work. Then his friend suggested trying a polygraph (lie detector test), which works by capturing sweat data, and he started to find some success. “I was shocked at how quickly I could go from capturing sweat data for myself and a few of my friends and then training this model that can essentially allow robots to have an emotional composition solely based on sweat data,” Warner said. He’s since expanded from sweat data into other areas, like body temperature, heart rate, and photoplethysmography, which measures the blood volume changes in the microvascular level of the skin, among others. Warner launched Intempus in September 2024 and spent the first four months exclusively on research. He’s spent the last few on a mix of building up these emotional capabilities for robots and engaging potential customers. He’s already signed seven enterprise robotics partners. Intempus is also part of the current cohort of Peter Thiel’s Thiel Fellowship program, which gives young entrepreneurs $200,000 over two years to drop out of school and build their companies. Warner said the next step for Intempus is to hire — he’s done everything until now as a team of one — and get some of the tech that’s already been built in front of humans to start testing. While Intempus is currently working on retrofitting existing robots and plans to focus on that, Warner said he’d never rule out Intempus building its own emotionally intelligent robots in the future. “I have a bunch of robots, and they run a bunch of emotions, and I want to have someone come in and just understand that this robot is a joyful robot, and if I can innately convey some emotion, some intents that the robot holds, then I’ve done my job properly,” Warner said. “I think I can, you know, really prove that I’ve done this over the next four to six months.”

Just 24 hours left to lock in Early Bird pricing for TechCrunch Disrupt 2025 — happening October 27–29 at Moscone West in San Francisco. Save up to $900 on your pass, or bring someone brilliant with you for 90% off their ticket. This deal ends tonight at 11:59 p.m. PT. Grab your Early Bird discount here — prices go up after tonight. You’ve probably seen the headlines. The speaker lists. The stats. Here’s what it all adds up to: 10,000 founders, investors, engineers, operators, and tech enthusiasts. 250+ main stage, breakout, and roundtable sessions. 200+ tech, startup, and VC heavyweights driving next-gen conversations. One ultimate ultimate startup showdown on a global stage — Startup Battlefield 200. But here’s what you won’t find on the Disrupt website: The sentence that rearranges your thinking. The handshake that shifts your career’s direction. The late-night conversation that sticks with you longer than the keynote. The spark that tells you: you’re not too early, you’re not too late — you’re right on time. That’s why thousands return to Disrupt year after year — 20 years strong. Disrupt is where tech gets loud — funding rounds, product reveals, stages full of brilliance. But underneath it all, it’s about momentum. Yours. Your startup’s. Your team’s. And if you’ve been waiting for a signal to go all-in? This is it. SAN FRANCISCO, CALIFORNIA – OCTOBER 28: (L-R) Alice Brooks, Rohan Ganesh, Galym Imanbayev, Corinne Riley and Oluseun Taiwo, Co-Founder & CEO of Solideon, speak onstage during TechCrunch Disrupt 2024 Day 1 at Moscone Center on October 28, 2024 in San Francisco, California.Image Credits:Kimberly White / Getty Images Last call: 2025 Disrupt discounts end in just hours This is your last chance to join the conversation, the collision, the next chapter in tech — live in San Francisco, October 27–29 — without paying full price. Techcrunch event Join us at TechCrunch Sessions: AI Secure your spot for our leading AI industry event with speakers from OpenAI, Anthropic, and Cohere. For a limited time, tickets are just $292 for an entire day of expert talks, workshops, and potent networking. Exhibit at TechCrunch Sessions: AI Secure your spot at TC Sessions: AI and show 1,200+ decision-makers what you’ve built — without the big spend. Available through May 9 or while tables last. Berkeley, CA | June 5 REGISTER NOW Time is almost up. What if you said “yes” to TechCrunch Disrupt 2025? Register before night ends at 11:59 p.m. PT to save up to $900 on you ticket and get the second for your +1 at 90% off. Secure your ticket savings to Disrupt 2025 here.

​​There are just 48 hours left to save up to $900 on your ticket to TechCrunch Disrupt 2025 — and get 90% off the second. After May 25 at 11:59 p.m. PT, Early Bird pricing vanishes — along with your best chance to join 10,000 of tech’s most forward-thinking minds for less. But forget the math for a moment. Let’s talk about what you actually get. From October 27–29, Moscone West in San Francisco transforms into a live-wire campus — a front-row seat to innovation. It’s high energy, yes — but also deeply human. Where else can startup founders pitch for a $100,000 equity-free prize on the same stage where CEOs from Luma AI, Flexport, Nextdoor, and GV unpack the next decade of tech? Where else do 1:1 and small-group Braindates and late-night Side Events coexist with six stages of live debate, big questions, and industry-shaping dialogue? This is where ideas become movements. Where the startup you invest in becomes the one your competitors envy. Where you finally understand what the AI evangelists have been trying to explain — or realize they’ve all missed the point. We’ll have 250+ sessions and speakers like: Astro Teller, Captain of Moonshots, X (The Moonshot Factory) Raquel Urtasun Founder and CEO, Waabi Alejandro Matamala Ortiz, Co-Founder and Chief Design Officer, Runway Techcrunch event Join us at TechCrunch Sessions: AI Secure your spot for our leading AI industry event with speakers from OpenAI, Anthropic, and Cohere. For a limited time, tickets are just $292 for an entire day of expert talks, workshops, and potent networking. Exhibit at TechCrunch Sessions: AI Secure your spot at TC Sessions: AI and show 1,200+ decision-makers what you’ve built — without the big spend. Available through May 9 or while tables last. Berkeley, CA | June 5 REGISTER NOW Nirav Tolia, Co-Founder & CEO, Nextdoor David George, General Partner, Andreessen Horowitz And many more big names in tech, startups, and VCs spanning six industry stages, breakouts, and roundtables. Each talk is curated to matter — and yes, you’ll find your people. Builders, thinkers, dreamers, doers. SAN FRANCISCO, CALIFORNIA – OCTOBER 30: Matt Mullenweg, Founder & CEO of Automattic, speaks onstage during TechCrunch Disrupt 2024 Day 3 at Moscone Center on October 30, 2024 in San Francisco, California. (Photo by Kimberly White/Getty Images for TechCrunch)Image Credits:Kimberly White / Getty Images So why wait? Every year, someone reads a post like this, decides to sit it out — and then texts a friend after seeing it all unfold online: “Should I have gone?” This is the moment where you choose not to ask that question later. Save up to $900 and get a second ticket for 90% off — but only until May 25 at 11:59 p.m. PT. Claim your TechCrunch Disrupt 2025 tickets before prices rise.

View File Blogar - Blog Magazine WordPress Theme Blogar is a trendy and trendy WordPress blog, magazine and blog theme with super flexibility and fully responsive design. Blogar is perfect for blog, creative blog, tech blog, lifestyle blog, magazine, SEO blog, news agencies, travel agencies, business magazines, lifestyle websites, and technology news websites. It is also suitable for any publishing or review website that requires a sleek, modern and clean look. To make sure it fits your business needs, we've tested our WordPress theme to adapt to whatever device your users are viewing it on, be it a laptop, mobile phone or tablet! Submitter CodeCanyon Submitted 05/25/25 Category Wordpress Templates Demo link https://themeforest.net/item/blogar-blog-magazine-wordpress-theme/30583777  

View File Marja - Fashion WooCommerce Theme Marja is a truly stunning eCommerce theme we designed for Multi-purpose websites. Aside from full WooCommerce compatibility, a gorgeous set of shop page layouts and elements is at your full disposal. If you want to create a dazzling fashion, jewelry, leather, kids store, auto parts, motor bikes, furniture, plants, electronic, organic, beauty or cosmetics shop website, look no further; Marja is here! Submitter CodeCanyon Submitted 05/25/25 Category Wordpress Templates Demo link https://themeforest.net/item/mina-modern-woocommerce-theme/41870207  

View File Auslogics BoostSpeed Portable Download Auslogics BoostSpeed from our website for free. BoostSpeed is your one-stop PC maintenance and optimization tool. It is the ideal solution to speed up your computer and Internet connection. The program will clean up, speed up and fix your slow computer to make it run as fast and stable as new. This powerful Windows optimizer also will boost Internet connections, tweak Windows to its peak performance, clean and defrag disks and the registry. It’s a great way to speed up your PC and keep it clean and optimized. Start programs faster. Speed up computer start time. Increase Internet speed, optimize your Internet Explorer, Firefox and E-mail programs. Auslogics “BoostSpeed” will clean up disks and the Registry to speed up your computer and tweak Windows to its peak performance. Modify Windows settings, file system and services to greatly increase system performance. Submitter CodeCanyon Submitted 05/25/25 Category Programs Demo link https://www.auslogics.com/en/software/boost-speed/  

View File MightyTaxi - Flutter Online Taxi Booking Full Solution Flutter is an open-source mobile application development SDK created by Google. It is used to develop applications for Android and iOS, as well as being the primary method of creating applications for Google Fuchsia, Flutter widgets incorporate all critical platform differences such as scrolling, navigation, icons and fonts to provide full native performance on both iOS and Android. From this codebase, You can make taxi booking app for your Business. Online taxi booking app is most useful features now a days. From this app, you can build your own taxi booking app. Submitter CodeCanyon Submitted 05/25/25 Category Android Demo link https://codecanyon.net/item/mightytaxi-flutter-online-taxi-booking-app-taxi-app-admin-backend-driver-app/40977853  

View File MightyStore WooCommerce - Flutter E-commerce Full App Flutter is an open-source mobile application development SDK created by Google. It is used to develop applications for Android and iOS, as well as being the primary method of creating applications for Google Fuchsia, Flutter widgets incorporate all critical platform differences such as scrolling, navigation, icons and fonts to provide full native performance on both iOS and Android. MightyStore app is universal app for e-commerce app build from Flutter framework that was developed by Google. This ultimate app saves a hefty amount of hours you should otherwise have to spend on designing, developing and testing. The ready-to-use UI design templates serves as a complete solution to launch your e-commerce shopping app. MightyStore is optimized to deliver the smart and functional app to build your e-commerce app. Additionally, the design elements and feature set helps you develop cost-efficient and highly productive way to work on your app project. If your business already have a website that is built based on WooCommerce framework, then MightyStore is best solution to build your mobile app. Submitter CodeCanyon Submitted 05/25/25 Category Android Demo link https://codecanyon.net/item/mightystore-woocommerce-universal-flutter-app-for-ecommerce-app/30218611  

View File Markite - Digital Marketplace WooCommerce WordPress Theme Markite is the digital marketplace WordPress theme to sell digital products, services, and others. Which is built based on WordPress and Most populer plugin WooCommerce. Using Markite digital marketplace theme, you can sell digital goods like stock photos, themes, plugins, software, music, ebooks, fonts files, and much more. It has been developed for Single and Multivnedor purposes. You can allow anybody to upload their digital items and sell them through your site by simply installing the Dokan Multivnedor plugin. It has unique and clean design based on the latest technology with great features. We’ve also used the most popular drag and drop page builder Elementor plugin to allows you to create your web pages quickly without knowing a single piece of code. Markite digital marketplace theme is heavily customized and organized for selling different kinds of digital goods. You can install Markite as like as our demo with just a single click. We’ve used one-click demo importer. Markite digital marketplace is very flexible to use your brand colour and Google fonts. You can easily change your brand colour and fonts from our theme settings. As well as you can easily pick your desire demo for your marketplace from among them and every day we are working on new demos and features. It’s available 40+ premium quality unique Elementor addons to use anywhere on your website. Using our rich features makes your marketplace more dynamic and vital. Available different import button for different versions means you can individually import your desire demo. Submitter CodeCanyon Submitted 05/25/25 Category Wordpress Templates Demo link https://themeforest.net/item/markite-digital-marketplace-woocommerce-theme/32633444  

View File Stockifly - Billing & Inventory Management with POS and Online Shop Stockifly is a billing and inventory management application for small to large scale business. It’s built using Vue and Laravel. Stockifly have all major features related to inventory like category, brand, products, sales, purchases, sales returns, purchase returns, stock Adjustment, expenses, customers, suppliers, roles, permissions, reports, billing, accounting and many more. Submitter CodeCanyon Submitted 05/25/25 Category Scripts Demo link https://codecanyon.net/item/stockifly-saas-billing-inventory-management-with-pos-and-online-shop/40754384  

View File WoWonder Android Messenger - Mobile Application for WoWonder Social Script WoWonder Android Messenger is an Android chat application for WoWonder PHP social network, with WoWonder Android Messenger users, can chat together on their mobile phones using our new application, now chat is faster, easier, and more fun! User Features: ِAudio/ Video call. Send, receive messages. Full Group chat system Find nearby users using GPS Registration pages and steps. Share & upload images, Sound Recourd. Offline access to all messages and recent conversions. Update chat status. Explore New user’s & Friends. Control Your Privacy. Control Your Settings. Change Profile information. Encrypted chat system. Pin & Archive chat conversation. Explore user’s profiles and status. ِ30+ new features. Submitter CodeCanyon Submitted 05/25/25 Category Android Demo link https://codecanyon.net/item/wowonder-android-messenger-mobile-application-for-wowonder/19034167  

View File Skote - React Admin & Dashboard Template + Sketch Skote is a fully featured premium admin dashboard template built in React & React Vite in Redux, Saga and Hooks with firebase / fack-backend and Facebook / Google authentication and multi-language supports with developer-friendly codes. We have not used jQuery in this template its pure ReactJs with CRA and fully components based admin template. Sketch, Figma & XD files are also available with this template. Skote is a beautifully crafted, clean & minimal designed admin template with Dark, Light Layouts with RTL options. You can build any type of web application like Saas based interface, eCommerce, CRM, CMS, Project management apps, Admin Panels, etc. It will help your team moving faster and saving development costs and valuable time. If you are a developer looking for a minimal admin dashboard that is fully responsive with Bootstrap and React, Redux, Saga, Hooks without jQuery, you are at the right place to start your project using Skote - React Admin Dashboard Template. Skote contains lots of new design widgets with responsive on all screens. Also, there are 7+ different types of Layouts we have added along with sidebar image and color changes options. It is very easy to change any layout in your existing running application by changing a couple of lines of code only as it’s managed with scss for Light, Dark and RTL and JSON object for all layouts. We have written standard and developer-friendly code to increase performance. Submitter CodeCanyon Submitted 05/25/25 Category Scripts Demo link https://themeforest.net/item/skote-react-admin-dashboard-template/26318700  

View File PeoplePro HRM, Payroll & Project Management by LionCoders PeoplePro HRM, Payroll & Project Management system is a comprehensive and cutting-edge software solution designed to streamline and optimize human resource management and project management processes within organizations. With its wide range of features and user-friendly interface, it empowers businesses to efficiently manage their workforce and projects, leading to increased productivity and improved overall performance. Submitter CodeCanyon Submitted 05/25/25 Category Scripts Demo link https://codecanyon.net/item/peoplepro-hrm-payroll-project-management/29169229