Family SUVs continue to dominate the market, but finding one that’s both affordable and genuinely reliable can be harder than it seems. With the average American now spending over $50,000 on a new car, shoppers are increasingly concerned about long-term costs. Fortunately, several standout models offer the space, safety, and everyday practicality families need, without the intimidating price tags.
Family sedans may not dominate headlines like SUVs, but in 2025 they offer some of the strongest value, comfort, and day-to-day usability on the market. With new models prioritizing quiet cabins, improved ride quality, and the latest driver-assist tech, shoppers who overlook this segment may be missing out on vehicles that deliver far more refinement than their price tags suggest.
Amazon is making more moves in the auto industry with a new partnership with Ford, allowing customers to buy certified preowned vehicles from the Detroit automaker directly on Amazon.com.
Shoppers in Los Angeles, Seattle and Dallas can browse certified Ford inventory from participating dealers within a 75-mile radius, complete most paperwork online, get financing — including through Ford Credit — and schedule a pickup time at a local franchised dealership.
“This program combines the trust and quality of a Ford-certified vehicle with the familiar, convenient shopping experience of Amazon,” Ford wrote in a blog post.
The launch follows a similar deal Amazon announced in 2023 with Hyundai, though that partnership included new vehicles. Amazon announced a separate deal with Hertz Car Sales earlier this year for used cars.
Hyundai AutoEver America was hacked in February and the attackers managed to steal SSNs and other personal data.
The post Automotive IT Firm Hyundai AutoEver Discloses Data Breach appeared first on SecurityWeek.
The technological landscape is evolving faster than ever. Two revolutionary forces Artificial Intelligence (AI) and Web3 are converging to reshape how humans, machines, and digital ecosystems interact. At the intersection of these innovations lies Decentralized-AI (dAI) a transformative concept that decentralizes the development, training, and governance of intelligent systems.
In the traditional world, AI has been controlled by centralized entities with exclusive access to massive datasets and computational power. Web3 challenges this imbalance by introducing decentralization, transparency, and user ownership. Together, dAI brings autonomy, fairness, and inclusivity to intelligence making it the foundation of the next digital era. This blog explores how Decentralized-AI (dAI) is powering the Web3 revolution, its architecture, benefits, and how it’s redefining trust and collaboration in the age of intelligent networks.
Traditional AI systems are built, trained, and managed by centralized corporations like Google, OpenAI, or Meta. These entities hold proprietary datasets, define algorithms, and control access effectively monopolizing innovation and outcomes.
Decentralized-AI (dAI) disrupts this model by distributing data ownership, computation, and decision-making across a network of participants. Instead of relying on a single authority, dAI leverages blockchain protocols, smart contracts, and distributed computing to create transparent and community-driven AI ecosystems.
Core Principles of dAI:
Transparency: Algorithms, models, and datasets are verifiable and open-source.
Fairness: Contributors are rewarded based on participation, not corporate hierarchy.
Autonomy: AI models can evolve and make decisions without centralized oversight.
Privacy: Data remains in the user’s control through cryptographic privacy layers.
This decentralized approach aligns perfectly with Web3’s core values openness, inclusivity, and ownership.
Web3 represents the third generation of the internet one built on blockchain technology that prioritizes user sovereignty over data and digital identity. Web3 transforms passive users into active participants by enabling token-based economies, decentralized storage, and autonomous governance.
When combined with AI, Web3 creates the infrastructure for trustless intelligence a network where:
✦AI models are trained collaboratively.
✦Data contributors retain control and ownership.
✦Model updates are governed via decentralized consensus.
✦Insights and outcomes are shared equitably among participants.
Thus, Web3 provides the infrastructure, and dAI provides the intelligence, together forming the backbone of an autonomous digital economy.
A) Blockchain for Trust and Transparency
Blockchain serves as the foundation for dAI, ensuring all training activities, model updates, and transactions are transparent and immutable. Every contribution from dataset sharing to computation can be recorded on-chain, creating a traceable and auditable AI ecosystem.
B) Federated Learning for Data Privacy
Instead of centralizing data, federated learning enables AI models to be trained across multiple devices or nodes without transferring sensitive information. Each node processes its own data locally and contributes only the learned insights, maintaining privacy and security.
C) Smart Contracts for Automation
Smart contracts automate the logic of AI collaboration such as compensating contributors, validating model updates, and enforcing governance rules without human intervention.
D) Tokenized Incentives
In dAI networks, tokens incentivize participation. Data providers, developers, and validators earn tokens for contributing computational resources, verifying updates, or improving AI models.
E) Decentralized Storage
AI models and datasets are stored using decentralized storage systems like IPFS or Arweave, preventing single points of failure and ensuring global accessibility.
The Web3 movement is centered around decentralization, ownership, and trustless interaction. dAI fits perfectly into this narrative by introducing intelligence that operates without central gatekeepers.
Here’s how dAI strengthens Web3 at its core:
A) Democratizing Intelligence
In centralized AI, intelligence is a closed asset owned by a few. dAI makes it community-owned, allowing developers, users, and contributors to participate in model creation and governance.
B) Enabling Self-Sovereign Data Economies
Web3 promotes data ownership, and dAI enables users to monetize their data directly by contributing to AI models. This transforms data from a passive asset into a source of income and influence.
C) Building Trustless Collaboration
By recording AI training and decision processes on the blockchain, dAI ensures transparency eliminating the “black box” problem of traditional AI.
D) Powering Autonomous Organizations (DAOs)
dAI agents can operate within Decentralized Autonomous Organizations (DAOs), making intelligent decisions, automating governance, and managing resources without centralized leadership.
E) Strengthening Web3 Infrastructure
From DeFi to NFTs to the Metaverse, dAI enhances functionality enabling smarter contracts, predictive analytics, adaptive user experiences, and personalized digital economies.
A) DeFi Optimization
Decentralized finance protocols use dAI for risk assessment, market prediction, and liquidity management all without centralized control.
B) Decentralized Autonomous Agents
dAI-powered agents can execute trades, moderate communities, manage digital assets, and interact with smart contracts autonomously.
C) NFT Market Intelligence
In NFT ecosystems, dAI analyzes trends, detects fraud, and automates curation to support transparent and efficient marketplaces.
D) Metaverse Integration
AI-driven avatars, NPCs, and environments in metaverse worlds can evolve independently using dAI frameworks that adapt based on user behavior.
E) Data Marketplaces
Users can share and monetize their anonymized data securely, fueling AI innovation while retaining control and ownership.
F) Decentralized Content Moderation
dAI enables decentralized platforms to moderate user-generated content transparently ensuring fairness without centralized censorship.
1. Transparency and Accountability
Every AI decision or update can be verified on-chain, ensuring clarity in model behavior and outputs.
2. Incentive Alignment
Token economies ensure that every contributor from data providers to validators benefits from network success.
3. Privacy Preservation
With encrypted learning techniques, users never lose control of their personal data.
4. Censorship Resistance
Since no central authority governs the network, dAI systems resist political or corporate manipulation.
5. Scalability and Collaboration
Global communities can co-create intelligent systems, accelerating innovation beyond corporate walls.
6. Autonomous Intelligence
AI models can self-govern, self-improve, and operate in distributed environments leading to true digital autonomy.
While dAI holds immense potential, it faces several challenges on its journey to mainstream adoption:
Computational Complexity: Decentralized networks require efficient ways to handle distributed AI training.
Standardization: Lack of unified protocols for dAI governance and integration slows collaboration.
Regulation: Balancing decentralization with compliance and ethics remains a gray area.
Security Risks: Open participation may expose vulnerabilities without proper verification layers.
Adoption Barrier: Developers need simplified tools and frameworks to deploy decentralized AI at scale.
Addressing these challenges will require collaboration between AI researchers, blockchain developers, and regulatory bodies to ensure security, scalability, and accessibility.
The coming decade will mark the rise of autonomous digital ecosystems.
Imagine AI agents that:
✦Negotiate contracts,
✦Manage decentralized funds,
✦Build dApps automatically, and
Adapt based on user interactions
all governed through transparent blockchain protocols.
This is the vision of Decentralized-AI (dAI) an era where machines collaborate with humans as equal participants in decentralized networks. In this ecosystem:
✦Ownership is shared,
✦Decisions are democratic,
✦Data is sovereign, and
✦Intelligence is distributed.
This shift represents not just a technological leap but a paradigm shift in how society defines control, innovation, and value.
Several pioneers are already pushing the boundaries of Decentralized-AI:
SingularityNET: A decentralized marketplace for AI services enabling global collaboration.
Fetch.ai: Autonomous agents for smart cities, logistics, and financial ecosystems.
Ocean Protocol: Data monetization and AI model sharing through decentralized exchanges.
Gensyn: Distributed compute network for AI model training.
Bittensor: A decentralized machine learning protocol that rewards network intelligence.
These initiatives are proving that intelligence can be open, distributed, and profitable without compromising privacy or fairness.
The integration of Decentralized-AI (dAI) and Web3 marks a defining moment in digital history. Together, they are dismantling centralized control and creating a world where data, intelligence, and innovation belong to everyone.
As the Web3 ecosystem matures, dAI will serve as its cognitive core powering automation, decision-making, and interaction across every decentralized layer.
In this new world, AI doesn’t just serve humans it collaborates with them.
It’s not owned by corporations but co-created by communities.
It’s not centralized but distributed.
And that’s what makes Decentralized-AI (dAI) the true core of the new Web3 era.
Why Decentralized-AI (dAI) Is the Core of the New Web3 Era? was originally published in Coinmonks on Medium, where people are continuing the conversation by highlighting and responding to this story.
Thandai cake is a fun Indian fusion dessert that combines the flavours of popular drink made on the festive occasion in India i.e Holi or Maha Shivratri. Thandai in the form of cake making it totally irresistible! Egg-free, buttress free, it’s easy to make, and absolutely delicious!
In this post sharing how to make this Holi special cake with step by step pics and video too!!
What is THandai
Thandai is a traditional Indian drink made with nuts, seeds and flavored with fragrant spices. This refreshing drink is popularly made on the festive occasion of Mahashivratri and Holi.
This Thandai Cake is
How to store Eggless thandai cake?
Thandai cake can be stored covered with foil paper(I have shown in my video, check it out how to store it) and refrigerated for up to a week or frozen for longer use. Allow cooling completely before storing.
PREP TIME :15 mins
COOK TIME :40 mins
TOTAL TIME : 55 mins
COURSE : Dessert
CUISINE : Indian
Author : Jolly Makkar
INGREDIENTS
For Thandai Cake
. All-purpose flour/ maida - 1 cup
. Granualted sugar - 1/3 cup + 1 tbsp
. Baking powder - 1 teaspoon
. Baking soda - 1/4 teaspoon
. A pinch teaspoon salt
. Thandai Powder - 2 tbsp
. Thick curd or Yogurt at room temperature - 1/2 cup
. Vegetable oil
. Warm milk - 1/4 cup + 2 tbsp
. Chopped Pistachios - 3 to 4
. Chopped Almonds - 5 to 6
INSTRUCTIONS:
1. To bake thandai cake, Preheat the oven to 350°F or 180 C. Lightly grease (spray oil) inside the cake tinand lining with butter paper and Keep aside.
2. Take warm milk in a bowl. Add thandai powder and mix well. Keep it aside at room temperature.
3. Sieve together flour, baking powder and baking soda in a bowl. Keep them aside.
4. In a bowl, take curd(yogurt) and add sugar to it. Whisk well till sugar is completely dissolved. Add thandai milk and oil. Whisk again for 6 to 8 minutes so that all wet ingredients mix properly.
5. Now its time to mixing DRY ingredients with WET ingredients together, divide into 3 parts and start mixing by using CUT and FOLD method. You can dry fruits in cake also, but I didn't add.
6. Once the batter is ready, pour it into cake tin and leveeled the cake with spatula.Tap the cake tin for 2-3 times to get rid of air bubbles. Garnish the cake with chopped almonds and pistachios.
7. Bake at 180 C for 30 minutes. Check the centre of the cake by using a toothpick or knife. If it comes out clean means cake is ready or If not bake for 2 more minutes.
8. Transfer it on wire rack to cool down completely and Enjoy the soft, delicious and lip smacking thandai cake with tea or coffee.
NOTES
⏺️For measuring your flour, do not scoop it out of the container directly using the measuring cup.
⏺️Thandai milk - I prefer making mine from scratch and highly recommend doing so but you can also use your favorite store-bought readymade thandai powder/masala to make your thandai.
⏺️Serving - You can serve this cake chilled (since thandai is usually served chilled) or warm it up in the microwave for 10-15 seconds to get it all warm and melty.
⏺️Storage - Thandai cake can be stored covered and refrigerated for up to a week or frozen for longer use. Allow cooling completely before storing.
Today, I am going to share a South Indian breakfast menu Idea or Pongal breakfast Menu idea. After a break of 1 and 1/4 years from blogging, I am sharing a Pongal-relevant post that is close to my heart. Pongal Festival In South India, on Pongal day, which falls in mid-January, i.e., on the first...How to make Thattai Vadai recipe ?
Thattai Vadai recipe is a popular snack that is quite popular in South India. Also known as Thattai Murukku, thattai recipe, nippattu recipe, nippat and Thattu Vadai. We used to prepare this often for Pongal, diwali, Krishna Jayanthi and other festival.
The post Thattai Vadai recipe – how to make thattai Murukku – Thattu vadai, Nippetu appeared first on Famous Indian Recipes.
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