graphicweave

10 things that happened in the tech world in 2024

Blog / / ,

10 things that happened in the tech world in 2024 1. AI Models and Generative AI Advancements The year 2024 witnessed significant advancements in generative AI, with groundbreaking developments by industry leaders OpenAI and Google. These innovations have reshaped the landscape of artificial intelligence, enabling more sophisticated applications across industries. OpenAI’s GPT-4.5 In 2024, OpenAI launched GPT-4.5, an incremental yet impactful upgrade from GPT-4. This version brought several enhancements: Improved Reasoning and ComprehensionGPT-4.5 exhibited better contextual understanding and multi-turn reasoning, making it more adept at complex tasks such as technical problem-solving, creative writing, and professional consultation. Multimodal Capabilities ExpansionWhile GPT-4 introduced multimodal input (processing text and images), GPT-4.5 refined these abilities. It could analyze images with greater accuracy and generate contextually relevant captions or interpretations, making it a stronger tool for visual data analysis. Speed and EfficiencyOpenAI optimized GPT-4.5 for faster response times and lower computational costs, ensuring smoother deployment in real-world applications. Dynamic Plugins IntegrationGPT-4.5 included enhanced plugin integration, allowing it to seamlessly interact with external tools, APIs, and databases. This feature broadened its utility in fields like business automation, education, and research. Google’s Gemini Google’s AI team introduced Gemini, their flagship generative AI model, as a direct competitor to OpenAI’s GPT-4. Gemini represented a paradigm shift with its emphasis on bridging the gap between human-like reasoning and real-world application: Unified Multimodal AIGemini excelled in unifying text, image, video, and even auditory inputs. This allowed it to handle complex scenarios requiring analysis and generation across multiple media types, making it a leader in immersive AI applications. Advanced Conversational AIWith innovations in dialog coherence, Gemini redefined conversational AI. It could sustain nuanced discussions, infer user intent more accurately, and provide contextually rich responses, setting a new standard in natural language processing. Real-Time World Knowledge UpdatesUnlike previous models with static knowledge bases, Gemini had real-time world knowledge updating capabilities. This made it more reliable for tasks like real-time news synthesis, financial forecasting, and global event analysis. Focus on AI Ethics and SafetyGoogle placed a strong emphasis on ethical AI development with Gemini. Advanced safety layers ensured reduced risks of misinformation, bias, and inappropriate content generation. 2. Mixed Reality and AR/VR Integration 2024 marked a pivotal year in the mixed reality (MR) and AR/VR landscape, with Apple Vision Pro and Meta’s Orion leading the charge. These two flagship devices epitomized the fusion of cutting-edge hardware, intuitive software, and immersive experiences, reshaping the way users interacted with both the physical and digital worlds. Apple Vision Pro: Redefining Mixed Reality Apple Vision Pro, unveiled in 2024, became a benchmark for AR/VR technology, combining sleek design with robust functionality. Apple positioned it as a “spatial computer,” emphasizing its role as a productivity and entertainment powerhouse. Key Features Unparalleled Display Technology Dual micro-OLED displays with a resolution exceeding 23 million pixels delivered stunning clarity, making virtual elements appear lifelike and seamlessly integrated with the real world. Wide color gamut and HDR support ensured vibrant visuals for movies, games, and professional applications. Eye and Hand Tracking Vision Pro introduced advanced eye-tracking sensors and infrared cameras, allowing users to control the interface with just their gaze and subtle gestures. No need for controllers—users interacted naturally by pointing, tapping, and swiping in the air. Spatial Audio Integration Personalized audio experiences were made possible with spatial audio, which mapped sound to the virtual environment. This feature enhanced immersion in virtual meetings, movies, and AR applications. Mixed Reality Mode A Digital Crown enabled seamless toggling between AR and VR modes, letting users control the level of immersion. Users could overlay apps and virtual objects onto their physical space while maintaining awareness of their surroundings. Productivity and Collaboration Vision Pro supported multiple virtual screens for multitasking, making it ideal for professionals. Integrated with Apple’s ecosystem, it allowed users to access Mac desktops, FaceTime, and iCloud in an immersive environment. Use Cases Entertainment: Watching 3D movies, immersive gaming, and interactive storytelling. Workspaces: Virtual monitors for professionals, collaboration via immersive FaceTime, and design tools for creatives. Health and Fitness: Guided workouts with holographic trainers and immersive wellness experiences. Meta’s Orion: Social-Centric Immersion Meta doubled down on its vision of the metaverse with the release of Orion, a mixed-reality device designed to connect users in immersive social and professional environments. Orion emphasized accessibility and deep integration with Meta’s platforms, including Facebook, Instagram, and Horizon Workrooms. Key Features High-Performance Hardware Equipped with a lightweight design, Orion utilized cutting-edge pancake optics for a slim profile. A powerful Snapdragon XR2 Gen 2 processor ensured smooth operation for both AR and VR applications. Full-Color Passthrough AR Unlike earlier Meta devices, Orion provided high-resolution color passthrough for AR experiences, enabling users to interact with their surroundings while engaging with virtual overlays. Meta Avatars 2.0 Enhanced avatars with realistic facial expressions, powered by AI-driven emotion recognition and improved sensors, made interactions more engaging and lifelike. Controller-Free Interaction Orion adopted hand-tracking technology, but users could also opt for lightweight haptic controllers for tasks requiring precision, such as gaming or creative work. Metaverse Integration Orion served as a gateway to Meta’s metaverse, enabling users to socialize, work, and shop in fully immersive environments. Use Cases Social Engagement: Hosting virtual meetups, parties, and shared experiences in Horizon Worlds. Gaming: Advanced multiplayer VR games with interactive social elements. Remote Work: Virtual offices and collaborative spaces designed for real-time interaction and productivity. E-Commerce: Virtual stores where users could browse, try, and purchase items using AR overlays.   3. Advanced Robotics and Automation The year 2024 marked a significant leap in advanced robotics and automation, with humanoid robots like Tesla’s Optimus making remarkable strides in performing industrial tasks. These robots bridged the gap between human dexterity and machine precision, driving efficiency and innovation across various industries. Tesla’s Optimus: Leading the Humanoid Revolution Tesla’s Optimus (also referred to as Tesla Bot) evolved from a prototype to a highly functional robotic assistant in 2024. Designed for versatility and cost-efficiency, Optimus was a humanoid robot tailored for industrial and general-purpose automation tasks. Industrial Applications of Optimus Manufacturing and Assembly

10 things that happened in the tech world in 2024 Read More »

Is AI Right for Your Company? A Guide to Making the Decision

Blog / /

Artificial intelligence (AI) has become one of the most talked-about technologies, with its ability to automate tasks, analyze vast data, and create personalized experiences. But is AI the right solution for every company? For organizations considering AI, here are some essential factors to weigh before deciding to adopt this technology. 1. Define Clear Business Goals The first question to ask is “What problem are we trying to solve?” AI isn’t a catch-all solution; it works best when aligned with specific business objectives. For instance, a company aiming to improve customer engagement might benefit from AI-powered chatbots or recommendation engines that personalize user interactions. Conversely, if current operations are running smoothly and efficiently, implementing AI might not add substantial value. A clear goal—whether it’s enhancing customer experience, optimizing internal operations, or increasing revenue—is essential for an AI project’s success. This clarity helps avoid costly, unnecessary projects that do not address business needs. 2. Assess Your Data Quality and Quantity AI thrives on data. Machine learning models and AI algorithms rely on large volumes of quality data to make accurate predictions, spot patterns, and automate decisions. Companies that already collect substantial, structured data (like customer behavior data, sales transactions, or operational logs) are well-positioned to benefit from AI. On the other hand, companies lacking data infrastructure may need to invest time and resources to capture, store, and organize data before seeing AI’s benefits. Furthermore, data quality is as important as quantity. Inconsistent, outdated, or irrelevant data can lead to flawed AI insights, potentially causing more harm than good. Assessing both the volume and integrity of data helps companies determine if AI implementation is feasible in the short term or if more foundational work is required. 3. Evaluate Resources and Expertise AI implementation is more than simply deploying a tool; it requires skilled resources to manage and optimize AI systems over time. AI initiatives need teams with expertise in data science, machine learning, and data engineering, as well as domain-specific knowledge. Companies with tech-savvy teams or data scientists are well-positioned to build, test, and refine AI models. For smaller organizations or those without in-house expertise, it may be beneficial to explore outsourced AI solutions or engage with AI consulting firms. Many providers offer pre-built AI solutions tailored to specific industries, which can make AI adoption easier and more accessible. 4. Weigh Initial Investment vs. Long-Term ROI AI projects often come with significant upfront costs, including technology, infrastructure, and talent. Many companies see AI as a long-term investment; the benefits, while substantial, may take time to materialize. Automating repetitive tasks may lead to immediate savings, while more complex implementations, such as predictive analytics or natural language processing, may take longer to deliver value. Estimating potential return on investment (ROI) is crucial. For example, a retailer using AI-driven demand forecasting might reduce stockouts and optimize inventory, leading to cost savings and improved customer satisfaction. Analyzing the expected ROI against the costs of implementation helps companies decide if AI adoption aligns with their financial goals. 5. Benchmark Against Industry Trends Looking at industry trends and competitor actions can provide insight into the benefits AI might bring to a particular sector. In industries like finance, retail, and healthcare, AI is widely adopted for applications such as fraud detection, personalized recommendations, and predictive diagnostics. In these sectors, AI can provide a competitive edge and may even be necessary to keep up with industry standards. However, in industries where AI adoption is still emerging, companies might be able to wait until technology becomes more cost-effective or better-suited for industry-specific needs. Staying informed about industry advancements allows companies to make timely and strategic decisions on AI. 6. Start with Scalable, Testable Solutions For companies uncertain about AI’s potential impact, a pilot or small-scale project can provide valuable insights. Starting with limited applications, such as automating data entry or deploying chatbots for customer support, allows a business to measure the impact and effectiveness of AI on a smaller scale. If the initial project delivers positive results, it can be scaled to more significant areas of the business. Scalable solutions allow companies to control risks and costs, refining AI capabilities gradually without making a large upfront commitment. This incremental approach also helps organizations learn from each phase, making it easier to integrate more complex AI solutions in the future. 7. Consider Ethical and Regulatory Factors AI adoption also brings ethical considerations, particularly regarding data privacy, bias, and transparency. Companies operating in highly regulated industries should carefully evaluate these factors, as certain AI applications may have compliance implications. For example, healthcare providers using AI for patient data analysis must comply with regulations like HIPAA, while financial firms must adhere to strict data governance standards. Ensuring AI systems are transparent, fair, and ethically sound can protect a company’s reputation and build trust among customers. This ethical assessment is essential for any company that wants to adopt AI responsibly. Conclusion Deciding if AI is right for your company involves careful consideration of your business needs, data readiness, available resources, and potential ROI. AI can unlock transformative benefits, but it’s not a one-size-fits-all solution. By thoughtfully assessing these factors and experimenting with small, scalable projects, companies can make well-informed decisions that align AI investments with long-term strategic goals. At GraphicWeave, before diving into a project for our clients we discuss the suitability and the best approach forward with our clients so they can make informed decisions. If you have an idea that you think could bring value with AI, let’s talk

Is AI Right for Your Company? A Guide to Making the Decision Read More »

JavaScript Style Guide.

Leave a Comment / Blog / / , , , ,

If you\’re like me, you earn your bread by writing JavaScript; Sometimes really good JavaScript and sometimes, JavaScript full of codesmell. Folks, it\’s about time we make use of something called as a style guide for our JavaScript (and React if you\’re into React/Vue or other big guns). But first things first. WHY THE HELL DO WE EVEN NEED THIS? Well, for the following reasons. • Your code will look amazing and will be readable by you even years down the line. • Your code will have very less non idiomatic parts. It\’ll automatically be somewhat good practice if you follow this style guide. For example, it will highlight an error in your IDE or your favorite text editor if you declared a useless function or a redundant variable. So by implementing a style guide, your IDE or editor will automatically tell you when you\’re writing bad JS and not just syntactically wrong JS even before you run a single line of code. • Two people won\’t be auto-aligning the same file with different formatting so as to form an unending cycle and countless git merge conflict cycles. (Trust me, that\’s something that has happened to me at my office) • Chances of messing up while writing code decrease exponentially. <br /> • Trust me, you\’ll be proud! 🙂 Ummm alright – But what\’s a style guide? It\’s a guide that recommends you on how to format and structure your code. Lint basically means to hint beforehand a bad practice or an error in your code. A style guide in JS can be implemented using eslint. Eslint is by far the most popular tool for code hinting in JS. (There\’s JSHint too but it isn\’t as popular) In eslint, there is a .eslintrc file we should use. It\’s basically a json file with a fancy name and it lives inside the root folder of our project. (alongside .babelrc and package.json) Touch this file and install the following dev packages to set up eslint in your next JS project. $ touch .eslintrc $ npm i eslint eslint-{config-airbnb,plugin-import} -D If it\’s React or ReactNative. Add another line. $ npm i eslint-{plugin-jsx-a11y,plugin-react} -D Let\’s use an .eslintrc file that I generally use which looks like this: { \”extends\”: \”airbnb\”, \”rules\”: { \”arrow-parens\”: \”off\”, \”global-require\”: \”off\”, \”indent\”: [ \”error\”, 4 ], \”no-console\”: \”off\”, \”comma-dangle\”: \”off\”, \”no-underscore-dangle\”: \”off\”, \”func-names\”: \”off\”, \”no-use-before-define\”: \”off\”, \”react/jsx-indent\”: [ \”error\”, 4 ], \”react/jsx-indent-props\”: [ \”error\”, 4 ], \”react/jsx-filename-extension\”: [1, { \”extensions\”: [\”.js\”, \”.jsx\”] }] } } Sidenote – There\’s an alternate way to configure eslint without the .eslintrc file. You can place a key called eslintConfig inside your package.json with a value same as that of the json that\’s inside your .eslintrc. This will however make your package.json file fat and it comes down to personal preference whichever technique you want to use. If my override rules are short, I prefer the package.json way where as if it\’s long, I\’m quite fine with the addition of the .eslintrc file. Now, after this comes the important part. Making our IDEs or text editors use this style guide and hint changes in our code on the fly inside its own UI. There\’re plenty of really good articles on this and I think I can point you to a few. (Skip the parts where they add the eslint itself to the project. We\’ve already done that, remember?) • For Atom – https://hackernoon.com/what-is-eslint-how-do-i-set-it-up-on-atom-70f270f57296. • For WebStorm – https://www.jetbrains.com/help/webstorm/eslint.html. • For Sublime – https://github.com/roadhump/SublimeLinter-eslint. There\’s google for others! Upon following this article, you and your the whole team (if they weren\’t grumpy enough to try this at the first place) will commit and write code that is beautifully formatted and according to the same style rules. Moreover, you can configure your IDE or text editor to automatically fix and format your files using the same style guide on every save! Neat huh?

JavaScript Style Guide. Read More »

×

Hello!

Click one of our contacts below to chat on WhatsApp

We build amazing stuff. Check our portfolio

× How can I help you?