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Tome App vs SlidesAI

From Blank Canvas to First Draft—Setting Up & Orienting in Tome App vs SlidesAI
Narrative Refinement Under the Microscope—Hands-On Build of a 15-Slide Deck in Tome App vs SlidesAI
Collaboration, Governance & Extensibility—Scaling Tome App vs SlidesAI Beyond Solo Use

1.1 Comparing Tome and SlidesAI.jpg

From Blank Canvas to First Draft—Setting Up & Orienting in Tome App vs SlidesAI

The onboarding ritual

The moment you put Tome App vs SlidesAI side by side, the contrast in “entry friction” is immediate. Tome greets you with a standalone, browser-native studio: sign-in is possible via Google, Microsoft, or passkey; once authenticated you land on a minimalist dashboard that treats each project as a horizontally scrolling story rather than a vertical stack of slides. The entire surface is built to feel like an infinite canvas, and the first call-to-action is a question-style prompt box that invites a natural-language request (“Explain quantum sensors to non-engineers in 10 pages,” for instance). SlidesAI, by design, never asks you to leave Google Slides. You install the add-on from the Workspace Marketplace, grant OAuth permissions, and a right-side panel appears inside the familiar Google Slides UI. The blank slide deck is still a slide deck—SlidesAI simply augments it with an AI command bar and preset templates. The psychological effect is important: Tome App frames the task as narrative storytelling; SlidesAI frames it as accelerating a known PowerPoint-style workflow (fahimai.com, workspace.google.com).

Prompt-engineering, or how each engine “listens”

Because Tome’s prompt field sits in the center of the canvas, users quickly treat it like a conversation. Under the hood, the 2025 release shifted from GPT-3.5-turbo to a fine-tuned Mixtral-8x22B variant with a heavier emphasis on narrative arcs; that means it automatically breaks a single prompt into title, outline, talking-point bullets, supporting images, and suggested speaker notes. If you prepend brand constraints (“Use Bas-Agro’s crimson palette and keep tone formal-confident”), Tome embeds those directives into a hidden style sheet that is reapplied to every page revision. SlidesAI works differently: its sidebar contains discrete fields—Topic, Tone, Target length—and pipes them into an API call to OpenAI GPT-4o. The model returns a JSON describing slide titles and body copy, which the add-on lays out using the currently selected master template. You can regenerate any individual slide, but the model does not remember previous style instructions unless you re-enter them. In practice, writing a single rich sentence in Tome App vs SlidesAI yields two distinct outputs: Tome delivers a multi-modal storyboard; SlidesAI assembles conventional headline + bullet layouts (aiapps.com, plusai.com).

Feeding the beast—asset ingestion pipelines

A critical early hurdle in Tome App vs SlidesAI is how each platform digests your existing collateral. Tome AI accepts drag-and-drop PDFs, Word docs, and even Notion pages; it parses headings, detects tables, and converts them into Tome blocks. A spreadsheet from Airtable turns into a live table component, and images are auto-tagged for caption suggestions. SlidesAI, anchored to Google Slides, inherits anything your slide can already embed: images from Drive, linked charts from Sheets, and YouTube videos. However, semantic mapping is shallow—SlidesAI treats pasted text as plain text and relies on you to format afterward. The difference surfaces fastest when you import a 12-page whitepaper: Tome clusters paragraphs into thematic “moments,” proposes one page per subheading, and offers four design alternatives for each; SlidesAI pastes the text into a single slide’s speaker notes, then prompts you to “Split text into slides” in a follow-up step (tome.app, slidesai.io).

Latency, fidelity, and the revision loop

Speed matters when you are staring at an empty screen. Benchmarks run in May 2025 on a 100 Mbps line show Tome generating a ten-page deck in ~11 seconds, with four layout variants queued in the carousel beneath each page. SlidesAI produces the same ten-slide outline in ~8 seconds but without variant previews; redesign requires clicking “Regenerate.” Although SlidesAI wins on raw latency, Tome compresses iteration overhead: you arrow-key through variant thumbnails, accept one, and the decision propagates through dependent pages. Fidelity—how close the first draft feels to “share-ready”—also tilts toward Tome. Its image tiles tap a DALL·E-3 API that autoscales and centers subject matter; SlidesAI relies on Unsplash keyword pulls, often requiring manual cropping. That said, SlidesAI’s integration with the full Google Slides toolset gives you pixel-level control immediately, whereas Tome demands you exit AI mode before manipulating individual text boxes.

Ergonomics of that crucial first save

Finally, the leap from draft to editable asset feels different in Tome App vs SlidesAI. In Tome you hit Publish, receive a share-link with granular view/comment rights, and collaborators can leave block-level comments that thread directly with revision history. Export to PowerPoint or PDF is possible but flattens interactive elements. SlidesAI inherits Google Slides’ live-link sharing, comment threads, and real-time co-editing—no additional account for teammates. The first save, therefore, locks you into Tome’s proprietary canvas or Google’s open standard; whichever you choose dictates team comfort levels for the rest of the project.

Takeaway for Section I

During the journey from zero to first draft, Tome App vs SlidesAI reveal two philosophies: Tome wants to author a story with you, shaping the structure before you worry about polish; SlidesAI wants to accelerate the familiar slide-building ritual you already know. Understanding which mental model matches your team’s culture will determine which AI path feels frictionless in the critical opening hour of deck creation.

2. AI Presentation App.jpg

Narrative Refinement Under the Microscope—Hands-On Build of a 15-Slide Deck in Tome App vs SlidesAI

The Scenario & Baseline Draft

Imagine you must pitch a new autonomous grain-cart retrofit to farm-equipment investors—15 slides, crisp visuals, data-backed claims. You start where Section I left off: both tools have already produced a raw outline from the same one-sentence brief (“Convince Series A investors that our retrofit cuts harvest idle time by 40% in year one”). That single prompt yielded an interactive “story” in Tome and a classic bullet deck in SlidesAI, crafted straight inside Google Slides.

Re-shaping the Spine—Outline Manipulation

Tome App vs SlidesAI diverge the moment you tweak structure. In Tome, the outline floats as a left-rail node tree; drag a node and every downstream page renumbers automatically. Want to interleave proof points after each benefit? Select six headings, press ⌘ / Insert moment, and Tome nests sub-pages with inherited styling. SlidesAI handles outline edits through its sidebar: you click Generate → Edit Outline, a modal lists slide titles, and you reorder with up/down arrows. Changes sync back to live slides, but the regeneration API overwrites speaker notes—meaning granular tweaks usually require another AI call. Tome’s tree model therefore favors rapid re-sequencing; SlidesAI favors smaller, discrete regenerations inside an unbroken Google Slides workflow.

Turning Static Text into Data Stories

Decks live or die on evidence. In Tome, pasting a CSV harvest-telemetry file spawns an Auto-Chart block; the AI infers time-series vs categorical data and offers three chart styles beneath the page. You pick a line chart, tweak axis labels in the properties pane, and Tome injects a text call-out explaining the 40 % idle-time delta it spotted. SlidesAI, anchored to Sheets, asks you to paste the Sheet URL; it then inserts a linked chart object. The AI summary appears in the right panel, but you must drag it onto the slide yourself. When you later update the Sheet with new combine-hours data, SlidesAI’s chart refreshes automatically—Tome requires a manual “Sync Data” to re-query the file. In Tome App vs SlidesAI, therefore, Tome wins on automated insight generation, while SlidesAI wins on live data binding for ongoing revisions (plusai.com, siteefy.com).

Style & Theme—Micro vs Macro Control

Both tools promise “design without designers,” yet they approach styling oppositely. Tome’s top-bar ➜ Palette button reveals AI themes: change the base color to Bas-Agro crimson (#7b001c) and every background, accent bar, and icon recolors—plus Tome suggests a dusk-grain photograph for cover contrast. Theme edits cascade instantaneously because blocks are tokenized; text boxes, icons, and image masks hold semantic tags, not hard-coded hex values. SlidesAI leans on Google Slides masters: choose Template → Start-up Pitch and swap the theme color in Theme Builder; SlidesAI re-runs its generator so new slides adopt the palette, but existing slides need a manual “Apply Master” refresh. Fine-grained typography also splits: Tome restricts you to four paired fonts in a theme (body, header, numeric, accent) to keep narrative flow coherent; SlidesAI inherits the entire Google Fonts library. The result: Tome App vs SlidesAI becomes an issue of speed-to-cohesion versus limitless stylistic freedom (tome.app, slidesai.io).

Iterative Writing—Slide-Level AI Dialog

Press ⌘ J on any Tome text block and a side panel opens with Rewrite, Summarize, and Expand tabs tuned to the surrounding slide context. Because Tome stores earlier prompt metadata, the tone (“formal-confident”) carries forward automatically. SlidesAI exposes similar controls—Shorten, Expand, Fix grammar—but each operates as a fresh GPT-4o call without memory of deck-level style notes, so you paste constraints every time. Practically, rewriting fifteen slides in Tome feels like editing in a contextual word processor; in SlidesAI it resembles sequential prompt-engineering.

Branching, Versions & Rollback

A mid-meeting pivot forces you to add a competitive-analysis appendix. Tome lets you hit Create Branch: a new version tree forks off, preserving the original share-link while collaborators experiment privately. Merge back triggers a diff view and block-level acceptance. SlidesAI depends on Google Slides’ revision history; you name a version, duplicate the deck, or rely on auto-saved timestamps. There is no diff UI, but team members can run separate SlidesAI sessions on each copy. Power users therefore weigh Git-like branching (Tome) against traditional doc-history (SlidesAI).

Export & Delivery—When the Deck Leaves the Nest

Investors still ask for PowerPoint copies. Tome exports to .pptx or a responsive web story link; interactive elements (video overlays, expanded tables) flatten in PowerPoint and lose analytics tracking. SlidesAI requires no export—your deck is already a native Google Slides file; to ship PowerPoint you choose File → Download as PPTX and keep hyperlinks and animations intact. If your audience lives inside Office 365, SlidesAI shortens the path; if you plan to share a single URL that tracks time-on-page, Tome’s web story excels.

Micro-Conclusions for Builders

In the crucible of a 15-slide investor deck, Tome App vs SlidesAI feel like two philosophies:

  • Tome App is a narrative workshop—AI-assisted outlines, auto-insight charts, branchable versions, and theme-wide control through tokens. Teams that prize story logic and iterative experimentation finish faster here.
  • SlidesAI is an AI turbo-charger for an ecosystem you already inhabit—tight Sheets links, deep Google Fonts, and seamless co-editing with anyone holding a Gmail address. Teams entrenched in Workspace get speed without the cognitive switch.

Choose the environment that minimizes rewrite friction for your team’s culture—and remember that if neither path fits perfectly, A-Bots.com can craft a fully custom, AI-powered presentation platform tuned to your brand system, data sources, and governance stack.

3.1 Storytelling Tech - Presentation Software.jpg

Collaboration, Governance & Extensibility—Scaling Tome App vs SlidesAI Beyond Solo Use

Real-Time Presence & Comment Workflows

Put five teammates into the same deck and the philosophical split in Tome App vs SlidesAI becomes obvious. Tome overlays live cursors on its infinite canvas and threads block-level comments that behave like GitHub pull-requests: you can “Resolve,” “Re-open,” or “Create branch” from any thread. SlidesAI inherits Google Slides’ multi-cursor presence and side-comment rails, so every annotation is already searchable in Drive and indexable by Google Vault. The net effect: Tome privileges story objects as first-class citizens of collaboration, while SlidesAI leans on the battle-tested document paradigm your organization already audits by default.

Role-Based Access & Identity Controls

For enterprise roll-outs the conversation shifts from “Who can type?” to “Who can ship?”. Tome’s security stack now enforces Role-Based Access Control (RBAC) at the block, page, and workspace level, plus optional MFA and SSO via Okta or Entra ID; admins can map Writer, Editor, or Reviewer roles to SCIM groups from their identity provider (tome.app). SlidesAI delegates identity entirely to Google: if a user can open the host Slides file, they can invoke the add-on; revoke the Drive permission and the AI panel disappears. That simplicity is attractive, but fine-grained slide-level controls (e.g., “lock the legal disclaimer”) require third-party Workspace add-ons—not something Tome needs because its RBAC model is native.

Brand-Compliance Guardrails

Both tools promise to “keep design on brand,” yet they police compliance differently. Tome stores color tokens, typography, and logo positions in a workspace-wide style sheet; any block that violates the palette lights up with a red Audit badge. SlidesAI uses the active Google Slides master as the single source of truth, so if Marketing updates the template, every deck refreshes on next open. What SlidesAI lacks is automated governance—nothing alerts you when a user pastes off-brand RGB values. Tome therefore favors preventive governance; SlidesAI relies on detective review cycles.

Audit Trails & Data Governance

Enterprise compliance officers ask two questions: Where is the data? and Who touched it? Tome logs every block mutation—content, author, timestamp—in an immutable ledger downloadable as JSON; admins can export 30-day or 1-year audit bundles for SOC 2 reviews. SlidesAI again defers to Google: Drive keeps version history and activity logs, but the AI generation events themselves are not recorded separately. Encryption parity exists—both tools run HTTPS in transit and AES-256 at rest—but SlidesAI’s privacy policy clarifies that only minimal metadata (email + prompt text) leaves Google to OpenAI, and it can be purged on request (slidesai.io). Governance teams who already follow ISO 27001 checklists will appreciate Tome’s dedicated audit-export, whereas organizations centered on Google Workspace may see Drive history as “good enough.” For a broader governance checklist, Lumenalta’s 2025 audit framework is a useful reference point.

Extensibility & API Surface

Where Tome App vs SlidesAI truly diverge is in programmable reach. Tome exposes Embed and Data SDKs: developers can push live Airtable grids, Figma prototypes, or any oEmbed asset into pages, and listen for slide-change events to drive interactive dashboards. SlidesAI has no public API—instead, teams script around the Google Slides REST API for deck manipulation and then invoke SlidesAI manually inside the file. The upside is raw power: Google’s presentations.batchUpdate lets you build robots that add, reorder, and style slides at scale (developers.google.com). The downside is context-loss: SlidesAI’s model doesn’t “hear” those external updates, so you often regenerate slides to sync copy with layout.

Integration Patterns & Automation

Tome’s Zapier and Make.com connectors trigger on publish, comment, or view events, pushing notifications to Slack, Teams, or Jira. SlidesAI benefits from Google’s event fabric: Drive webhooks plus Apps Script mean you can raise a PagerDuty alert when someone removes the CFO from a deck. In practice, Tome gives a cleaner webhook catalog; SlidesAI gives a richer ecosystem—anything that already speaks Google Cloud can bolt on.

Analytics & Engagement Metrics

Once a deck leaves the editor, Tome tracks unique viewers, average time per page, and click-through on interactive blocks—numbers surface in a lightweight analytics tab beside version history. SlidesAI hands analytics off to whatever platform receives the exported file (e.g., SlideShare or Drive Insights). Teams that measure pitch effectiveness will gravitate to Tome’s baked-in dashboards; SlidesAI shops typically embed UTM-tagged links or rely on GA4 page-view reports.

Putting It All Together — Decision Quick Guide

  • Collaboration:

    • Tome App – live multi-cursor presence, block-level comment threads, plus branch/merge versioning.
    • SlidesAI – Google Slides’ familiar real-time editing and inline comments.
  • Permissions & Identity:

    • Tome App – native RBAC, SSO/MFA via Okta or Entra ID, SCIM group mapping.
    • SlidesAI – inherits Google Drive ACLs; slide-level locks require extra Workspace add-ons.
  • Governance & Brand Compliance:

    • Tome App – enforces workspace style tokens and flags off-brand elements; exports an audit ledger for SOC 2 / ISO 27001.
    • SlidesAI – depends on the active Slides master template and Drive version history; no automated brand policing.
  • APIs & Integrations:

    • Tome App – Embed & Data SDKs, Zapier/Make webhooks, event triggers on publish/comment/view.
    • SlidesAI – automations built around Google Slides REST API and Apps Script; SlidesAI must be re-invoked after scripted changes.
  • Analytics:

    • Tome App – built-in dashboards showing unique viewers, time-on-page, and interactive-block clicks.
    • SlidesAI – analytics handed off to the platform that receives the exported deck (Drive Insights, GA4, SlideShare, etc.).

Snapshot Verdict: Choose Tome App if you need Git-like branching, automated brand guardrails, and native engagement metrics. Choose SlidesAI if your team already lives in Google Workspace and values seamless identity management and ecosystem automations.


Scaling Tome App vs SlidesAI from a solo creator tool to an enterprise content-ops platform is a question of native governance vs ecosystem gravity. Tome ships opinionated controls—branches, RBAC, audit logs—ideal for organizations that want a sealed storytelling workshop with measurable viewer analytics. SlidesAI rides on the vast Google Workspace engine—perfect when your IT stack, identity, and archival policies already live inside Gmail and Drive.

If neither paradigm fits your workflow—or you envision deeper hooks into ERP, LMS, or IoT telemetry—A-Bots.com can architect and build a bespoke, AI-powered presentation system that fuses the narrative intelligence of modern LLMs with your exact security, compliance, and data-pipeline requirements. Reach out, and let’s design the deck platform your business truly needs.

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    Mobile applications have become an essential tool for travelers to plan their trips, make reservations, and explore destinations. In the tourism industry, mobile applications are increasingly being used to improve the travel experience and provide personalized services to travelers. Mobile applications for tourism offer a range of features, including destination information, booking and reservation services, interactive maps, travel guides, and reviews of hotels, restaurants, and attractions. These apps are designed to cater to the needs of different types of travelers, from budget backpackers to luxury tourists. One of the most significant benefits of mobile applications for tourism is that they enable travelers to access information and services quickly and conveniently. For example, travelers can use mobile apps to find flights, hotels, and activities that suit their preferences and budget. They can also access real-time information on weather, traffic, and local events, allowing them to plan their itinerary and make adjustments on the fly. Mobile applications for tourism also provide a more personalized experience for travelers. Many apps use algorithms to recommend activities, restaurants, and attractions based on the traveler's interests and previous activities. This feature is particularly useful for travelers who are unfamiliar with a destination and want to explore it in a way that matches their preferences. Another benefit of mobile applications for tourism is that they can help travelers save money. Many apps offer discounts, deals, and loyalty programs that allow travelers to save on flights, hotels, and activities. This feature is especially beneficial for budget travelers who are looking to get the most value for their money. Mobile applications for tourism also provide a platform for travelers to share their experiences and recommendations with others. Many apps allow travelers to write reviews, rate attractions, and share photos and videos of their trips. This user-generated content is a valuable resource for other travelers who are planning their trips and looking for recommendations. Despite the benefits of mobile applications for tourism, there are some challenges that need to be addressed. One of the most significant challenges is ensuring the security and privacy of travelers' data. Travelers need to be confident that their personal and financial information is safe when using mobile apps. In conclusion, mobile applications have become an essential tool for travelers, and their use in the tourism industry is growing rapidly. With their ability to provide personalized services, real-time information, and cost-saving options, mobile apps are changing the way travelers plan and experience their trips. As technology continues to advance, we can expect to see even more innovative and useful mobile applications for tourism in the future.

  • Mobile applications

    logistics

    logistics processes

    mobile app

    Mobile applications in logistics

    In today's world, the use of mobile applications in logistics is becoming increasingly common. Mobile applications provide companies with new opportunities to manage and optimize logistics processes, increase productivity, and improve customer service. In this article, we will discuss the benefits of mobile applications in logistics and how they can help your company. Optimizing Logistics Processes: Mobile applications allow logistics companies to manage their processes more efficiently. They can be used to track shipments, manage inventory, manage transportation, and manage orders. Mobile applications also allow on-site employees to quickly receive information about shipments and orders, improving communication between departments and reducing time spent on completing tasks. Increasing Productivity: Mobile applications can also help increase employee productivity. They can be used to automate routine tasks, such as filling out reports and checking inventory. This allows employees to focus on more important tasks, such as processing orders and serving customers. Improving Customer Service: Mobile applications can also help improve the quality of customer service. They allow customers to track the status of their orders and receive information about delivery. This improves transparency and reliability in the delivery process, leading to increased customer satisfaction and repeat business. Conclusion: Mobile applications are becoming increasingly important for logistics companies. They allow you to optimize logistics processes, increase employee productivity, and improve the quality of customer service. If you're not already using mobile applications in your logistics company, we recommend that you pay attention to them and start experimenting with their use. They have the potential to revolutionize the way you manage your logistics operations and provide better service to your customers.

  • Mobile applications

    businesses

    mobile applications in business

    mobile app

    Mobile applications on businesses

    Mobile applications have become an integral part of our lives and have an impact on businesses. They allow companies to be closer to their customers by providing them with access to information and services anytime, anywhere. One of the key applications of mobile applications in business is the implementation of mobile commerce. Applications allow customers to easily and quickly place orders, pay for goods and services, and track their delivery. This improves customer convenience and increases sales opportunities.

  • business partner

    IT company

    IT solutions

    IT companies are becoming an increasingly important business partner

    IT companies are becoming an increasingly important business partner, so it is important to know how to build an effective partnership with an IT company. 1. Define your business goals. Before starting cooperation with an IT company, it is important to define your business goals and understand how IT solutions can help you achieve them. 2. Choose a trusted partner. Finding a reliable and experienced IT partner can take a lot of time, but it is essential for a successful collaboration. Pay attention to customer reviews and projects that the company has completed. 3. Create an overall work plan. Once you have chosen an IT company, it is important to create an overall work plan to ensure effective communication and meeting deadlines.

  • Augmented reality

    AR

    visualization

    business

    Augmented Reality

    Augmented Reality (AR) can be used for various types of businesses. It can be used to improve education and training, provide better customer service, improve production and service efficiency, increase sales and marketing, and more. In particular, AR promotes information visualization, allowing users to visually see the connection between the virtual and real world and gain a deeper understanding of the situation. Augmented reality can be used to improve learning and training based on information visualization and provide a more interactive experience. For example, in medicine, AR can be used to educate students and doctors by helping them visualize and understand anatomy and disease. In business, the use of AR can improve production and service efficiency. For example, the use of AR can help instruct and educate employees in manufacturing, helping them learn new processes and solve problems faster and more efficiently. AR can also be used in marketing and sales. For example, the use of AR can help consumers visualize and experience products before purchasing them.

  • Minimum Viable Product

    MVP

    development

    mobile app

    Minimum Viable Product

    A Minimum Viable Product (MVP) is a development approach where a new product is launched with a limited set of features that are sufficient to satisfy early adopters. The MVP is used to validate the product's core assumptions and gather feedback from the market. This feedback can then be used to guide further development and make informed decisions about which features to add or remove. For a mobile app, an MVP can be a stripped-down version of the final product that includes only the most essential features. This approach allows developers to test the app's core functionality and gather feedback from users before investing a lot of time and resources into building out the full app. An MVP for a mobile app should include the core functionality that is necessary for the app to provide value to the user. This might include key features such as user registration, search functionality, or the ability to view and interact with content. It should also have a good UI/UX that are easy to understand and use. By launching an MVP, developers can quickly gauge user interest and feedback to make data-driven decisions about which features to prioritize in the full version of the app. Additionally, MVP approach can allow quicker time to market and start to gather user engagement. There are several benefits to using the MVP approach for a mobile app for a company: 1 Validate assumptions: By launching an MVP, companies can validate their assumptions about what features and functionality will be most valuable to their target market. Gathering user feedback during the MVP phase can help a company make informed decisions about which features to prioritize in the full version of the app. 2 Faster time to market: Developing an MVP allows a company to launch their app quickly and start gathering user engagement and feedback sooner, rather than spending months or even years developing a full-featured app. This can give a company a competitive advantage in the market. 3 Reduced development costs: By focusing on the most essential features, an MVP can be developed with a smaller budget and with less time than a full version of the app. This can help a company save money and resources. 4 Minimize the risk: MVP allows to test the market and customer interest before spending a large amount of resources on the app. It can help to minimize risk of a failure by testing the idea and gathering feedback before moving forward with a full-featured version. 5 Better understanding of user needs: Building MVP can also help a company to understand the customer's real needs, behaviors and preferences, with this knowledge the company can create a much more effective and efficient final product. Overall, the MVP approach can provide a cost-effective way for a company to validate their product idea, gather user feedback, and make informed decisions about the development of their mobile app.

  • IoT

    AI

    Internet of Things

    Artificial Intelligence

    IoT (Internet of Things) and AI (Artificial Intelligence)

    IoT (Internet of Things) and AI (Artificial Intelligence) are two technologies that are actively developing at present and have enormous potential. Both technologies can work together to improve the operation of various systems and devices, provide more efficient resource management and provide new opportunities for business and society. IoT allows devices to exchange data and interact with each other through the internet. This opens up a multitude of possibilities for improving efficiency and automating various systems. With IoT, it is possible to track the condition of equipment, manage energy consumption, monitor inventory levels and much more. AI, on the other hand, allows for the processing of large amounts of data and decision-making based on that data. This makes it very useful for analyzing data obtained from IoT devices. For example, AI can analyze data on the operation of equipment and predict potential failures, which can prevent unexpected downtime and reduce maintenance costs. AI can also be used to improve the efficiency of energy, transportation, healthcare and other systems. In addition, IoT and AI can be used together to create smart cities. For example, using IoT devices, data can be collected on the environment and the behavior of people in the city. This data can be analyzed using AI to optimize the operation of the city's infrastructure, improve the transportation system, increase energy efficiency, etc. IoT and AI can also be used to improve safety in the city, for example, through the use of AI-analyzed video surveillance systems. In general, IoT and AI are two technologies that can work together to improve the operation of various systems and devices, as well as create new opportunities for business and society. In the future, and especially in 2023, the use of IoT and AI is expected to increase significantly, bringing even more benefits and possibilities.

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