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Gemini Google AI – Everything you need to know

gemini1

Until recently, OpenAI dominated the world of artificial intelligence (AI) and chatbots, with its GPT-4 large language model (LLM) powering Microsoft's ChatGPT and Copilot. OpenAI's early leadership kept others playing catch-up.

However, OpenAI now faces a new challenger: Google Gemini. Launching in February 2024, following its announcement in late 2023, Gemini quickly made significant waves in the AI landscape.

But will it be enough to overcome GPT-4? What capabilities does Gemini have now and what can we expect in the future? And how can you start using this tool?

We explored Gemini in depth to answer these questions and more. If you're curious about Google's latest AI, this is the place to be.

What is Google Gemini?

What is Google Gemini?

Gemini is Google's latest large language model (LLM). An LLM is a system that supports various AI tools that you've probably found online.

For example, GPT-4 powers ChatGPT Plus, OpenAI's advanced paid chatbot.

Being more than just an AI model; it has also taken on the new identity of the chatbot Bard.

Therefore, Bard was completely replaced by Gemini, unifying the underlying model and the chatbot under one name.

Google has also released a free Android app that can replace Google Assistant on your phone. On iOS, this tool appears in the Google app.

Additionally, Google has rebranded its Duet AI service for businesses as Gemini for Workspace, offering a suite of productivity-related features.

There is also a subscription service, Gemini Advanced, powered by a more robust LLM called Gemini Ultra.

In short, all of Google's AI properties are now unified under the Gemini umbrella, simplifying access, whether for consumers or businesses, via web, smartphone assistant or app.

What does Gemini AI do?

What does Gemini AI do 2

In short: a lot. It covers a wide range of AI capabilities delivered across multiple platforms.

Google describes Gemini as a multimodal tool, capable of handling multiple forms of input and output, including text, code, audio, images and videos. This versatility allows you to perform a wide range of tasks.

Google has implemented two separate LLMs: Gemini 1.0 Pro, which powers the free version, and 1.0 Ultra, which powers the Advanced subscription service.

While the free Pro version is simpler and less creative, the paid Ultra offers deeper, more accurate answers and management of complex tasks like coding.

Gemini Pro can answer simple questions, summarize text, and create images. It integrates with other Google services, such as Gmail, Google Maps, and YouTube.

For example, asking for sightseeing recommendations will yield results on Google Maps.

The app on Android can replace Google Assistant, handling queries and integrating with other Google services. However, Gemini has its limitations.

It can be slower than Google Assistant and still has bugs, such as inconsistent interaction with photos.

Despite these issues, Google is rapidly improving functionality on mobile devices.

Gemini Ultra, the subscription model, offers advanced features including handling queries in multiple stages and providing more accurate and organized responses.

It will soon be integrated into Google Docs, Gmail, and other productivity apps for advanced subscribers.

Looking ahead, Google is already working on its next-generation model, Gemini 1.5, which will improve both LLMs.

Early tests of the Pro version show dramatic improvements, such as extracting comical moments from a 400-page Apollo 11 transcript in just 30 seconds.

When was it released?

Google Gemini was launched on February 8, 2024, replacing Bard. It was immediately available in free and paid versions, with the Android app launching in the US.

The iOS app is now available on the Google app, albeit in a more limited form compared to Android.

Is Google Gemini free?

How much does Gemini Advanced cost?

Google's standard version is free, but it's more limited than the paid version, Gemini Advanced.

The subscription costs R$96.99 per month, with a two-month free trial available. This subscription is part of the Google One AI Premium plan.

It also includes 2 TB of cloud storage and other benefits.

So, given that Google One with 2TB storage already costs R$38.99 per month, the Advanced subscription offers substantial value for those who need cloud storage.

How do I use it?

What is Google Gemini for?

Using Google Gemini depends on the version and product it is integrated with. You can use AI directly on the official website or through the app.

The app is available on your Android phone, where it can replace Google Assistant. On iOS, it works on the Google app. Additionally, you can subscribe to Gemini Advanced for a more powerful AI experience.

Gemini vs. GPT-4: What's the difference?

How does Gemini compare to GPT-4 in the competition of large language models? When Google first revealed Gemini, it stated that it surpassed GPT-4 in several benchmarks.

Google reported that Gemini outperformed GPT-4 in seven of eight text-based benchmarks and all ten multimodal benchmarks.

However, since GPT-4 launched in March 2023, Gemini is essentially catching up to a nearly year-old rival.

In conclusion, although this technology has quickly become a significant player in the AI landscape, competition with GPT-4 and future models remains fierce.

gemini vs chatgpt

In short, Google Gemini represents a significant advancement in the AI landscape, offering a versatile and powerful set of tools that rivals the established dominance of OpenAI's GPT-4.

Therefore, with your comprehensive integration between applications consumer and business, this technology has positioned itself as a formidable competitor.

Although it still faces challenges and limitations, especially in its free version, the rapid improvements and the promise of future updates like version 1.5 point to a bright future.

So, as the field of AI continues to evolve, the competition between Google Gemini and OpenAI's GPT-4 will drive innovation, ultimately benefiting users with more sophisticated and capable AI solutions.

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Neto Camarano

Neto specialized in Bubble due to the need to create technologies quickly and cheaply for his startup. Since then, he has been creating systems and automations with AI. At the Bubble Developer Summit 2023, he was listed as one of the greatest Bubble mentors in the world. In December, he was named the largest member of the global NoCode community at the NoCode Awards 2023 and first place in the best application competition organized by Bubble itself. Today, Neto focuses on creating AI Agent solutions and automations using N8N and Open AI.

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The market is changing – fast. Artificial intelligence is no longer a trend, it has become a necessity. Companies are cutting costs, optimizing operations and looking for specialists to implement AI in their daily lives. And this is exactly where the AI profession comes in. AI Manager Course.

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Artificial intelligence (AI) is reshaping the way the financial sector operates, from risk analysis to the automation of complex processes. More than a trend, AI has become a strategic tool for financial institutions that want to increase their efficiency, reduce costs and offer personalized experiences. Within this scenario, the use of AI agents for finance has been gaining ground as a practical and accessible application for companies of all sizes.

Financial dashboard with automated charts and visuals representing artificial intelligence

AI Software Development in the Financial Sector

Creating AI-based solutions in the financial context requires robustness, security, and adaptability. Developing this type of software requires an architecture that is prepared to handle large volumes of data, continuous learning, and the ability to provide accurate insights.

In addition, systems need to be able to handle sensitive data, integrate with multiple sources (such as banks, brokerages, and ERPs), and adapt quickly to regulatory changes in the industry. Flexibility and modularity are core elements of any AI architecture for finance.

Integration with Existing Infrastructures

Much of AI’s success in the financial sector depends on its integration with legacy systems. This includes internet banking platforms, CRMs, payment gateways, and compliance tools. Using NoCode platforms such as make up or N8N allows you to create effective connections without the complexity of traditional development.

By the way, if you want to experience in practice how to integrate financial flows with AI, No-Code Start-Up provides a free N8N course with full video on YouTube. It's a great opportunity to explore real automations and understand how to structure secure and intelligent integrations in an accessible way.

With this approach, banks and fintechs can activate intelligent flows based on real data, such as automatic sending of alerts, personalized segmentations and recommendations based on consumer behavior.

Challenges in AI Development for the Financial Sector

Despite the enormous potential, there are challenges that need to be considered. Among the most relevant are:

  • Data quality: models are only effective if fed by clean and organized data.
  • Explainability: It is essential to understand how the AI arrived at a particular recommendation.
  • Cultural resistance: Traditional teams may resist adopting automation and algorithm-based decisions.

As highlighted by Deloitte, the combination of data governance, team training and ethical monitoring of AI is essential to mitigate risks and generate consistent results.

Security and Regulatory Compliance

The financial sector is one of the most regulated in the world. Therefore, all AI applications must comply with standards such as LGPD, GDPR and Central Bank regulations.

The adoption of good practices Data Privacy by Design, end-to-end encryption and role-based access control are just some of the basic requirements. Platforms such as Xano offer robust infrastructure with a focus on security for those who want to develop financial backends with AI.

Digital security illustration with padlock and financial data, symbolizing protection and compliance in AI application

Software Scalability and Resilience

As AI becomes a critical part of operations, it is necessary to ensure that systems are scalable and resilient. This means being able to grow as demand dictates, without compromising performance or security. Cloud computing and the adoption of microservices are essential strategies in this journey.

Companies like Goldman Sachs and Bank of Brazil have already demonstrated, in different contexts, how AI models can be deployed gradually, safely testing hypotheses before scaling to the entire operation.

AI Agents for Finance: Use Cases and Applications in the Financial Sector

1. Automated credit analysis

Companies like Credits use AI to evaluate hundreds of variables — including banking history, spending habits, and public data — to offer personalized credit. This reduces default rates and expands access to credit in a fairer way. According to McKinsey, automation can reduce analysis time by up to 70%.

2. Fraud prevention

O Bradesco and other institutions have implemented machine learning models that detect fraud based on behavioral patterns. When a transaction deviates from the pattern, the system triggers an automatic block or sends an additional verification to the user. According to Visa, the use of artificial intelligence helps prevent fraud totaling approximately US$14T25 billion.

3. Automated investment management

Robo-advisors like the ones from XP Investments use algorithms that analyze investor profiles, financial goals and market conditions to assemble and rebalance portfolios autonomously. CB Insights highlights that these systems are democratizing access to quality financial services, previously restricted to large investors.

4. AI-powered customer service

O Itau has incorporated AI into its digital channels, allowing customers to renegotiate debts, request second copies of bills or consult invoices using natural language. This reduces response time, improves customer experience and frees up human teams for more complex cases. According to Accenture, up to 80% of first-level banking interactions can now be automated using artificial intelligence.

5. Cash flow forecast

Financial management startups use AI agents for finance that integrate data on accounts payable and receivable, seasonality and market trends to predict cash flow for the coming months with high accuracy. Based on this information, more assertive decisions can be made. Harvard Business Review reinforces that this approach reduces the margin of error in financial projections and improves strategic planning.

The Role of AI Agents for Finance

Among all the applications, the AI agents for finance stand out for their versatility and accessibility. They function as intelligent “copilots”, performing tasks such as:

  • Automatic generation of financial reports
  • Sending alerts about targets or deviations
  • Predictive profitability analysis

Using platforms such as Dify and OpenAI, it is possible to configure these agents with natural language, making them easier to use even for those without technical training. This expands access to data intelligence in the financial sector.

The Future of AI in the Financial Sector

Artificial intelligence in the financial sector is no longer a distant promise — it is present in strategic decisions, customer service, and risk management. The adoption of technologies like AI agents for finance represents a leap forward in digital maturity. As technical challenges are overcome and platforms become more accessible, companies of all sizes will be able to use AI not only to automate, but to evolve.

Organizations that master the use of AI ethically, safely, and strategically will be ahead in delivering value and conquering the market. The future of finance is predictive, integrated, and data-driven — and it starts now. Want to learn how to build your own AI-powered financial agents without coding? Access the AI Agent Manager Training and discover the most practical way to apply all this in your context.

How AI is changing the market can be observed in practically all sectors of the economy, and this change is intensifying every day. Artificial intelligence (AI) is being recognized as a disruptive force that is profoundly reshaping the global market. From simple tasks to complex decisions, it has been integrated into processes in various sectors, transforming the way people work, consume and manage businesses.

Furthermore, when observing the effects of this transformation, it becomes clear how much the job market is being reconfigured: new opportunities arise, some professions lose ground and others adapt or are reborn with the support of technology, which demonstrates how AI is changing the market in a broad and profound way.

How AI is changing the job market

AI is accelerating the automation of repetitive and operational tasks. AI systems are already being used to efficiently perform:

  • Customer service with chatbots.
  • Predictive data analysis for sales and marketing.
  • Automated financial and audit processes.
  • Inventory control and logistics.

These changes not only reduce operational costs, they also require the workforce to be retrained for new roles, which reinforces how AI is changing the job market with great intensity.

Representation of people and artificial intelligence collaborating in different professions

Professions affected by artificial intelligence

According to PwC's report on the future of work (source), it is estimated that up to 30% of human tasks could be automated by the mid-2030s. This data shows, in practice, how AI is changing the job market and skills requirements.

Some of the roles most impacted by AI include:

  • Telemarketing operators
  • Administrative assistants
  • Data Analysts (some tasks being replaced by generative AI)

On the other hand, new functions emerge, such as:

  • Prompt Engineers
  • Automation experts with NoCode
  • Conversational Experience Designers
  • Intelligent Agent Managers

Those AI agents, for example, have been increasingly used in companies seeking to automate decisions and perform tasks with minimal human intervention. According to an analysis of the The Verge, large companies such as OpenAI, Google and DeepMind are investing heavily in the development of these systems, which can already act independently in complex corporate processes. They are designed to operate autonomously, learn continuously and integrate with other technologies — which makes them key players in the ongoing digital transformation.

What's Happening Now: How AI is Changing the Marketplace in Numbers

The AI market is experiencing exponential growth. The sector is estimated to surpass US$ 500 billion in value by 2027. There is a global race for innovation, with startups, large companies and governments investing heavily in:

  • Generative models (like ChatGPT)
  • Robotic Process Automation (RPA)
  • Artificial intelligence applied to health, education, law and agribusiness

This movement demonstrates how AI is being positioned as a strategic asset for growth and competitiveness.

Suggested reading:

AI Agent and Automation Manager Training

What are the negative aspects of AI in the job market?

Despite promising advances, important challenges also arise:

  • Structural unemployment: functions terminated without sufficient time for requalification
  • Digital inequality: not everyone has access to technological education
  • Technological dependence: companies become hostages of platforms and algorithms
  • Ethical and privacy issues: inappropriate use of data and biased automated decisions

These factors require public policies, business leaders and civil society to debate limits, transparency and responsibilities in the use of technology.

People using AI tools in a modern workplace

Opportunities and the future of work with AI

The key is in the conscious adaptation. The future of work will be driven by:

  • Continuous learning and professional requalification
  • Mastery of AI tools and NoCode platforms
  • Creating new business models based on data and automation
  • Development and management of autonomous AI agents

Increasingly, professionals and companies will need to adopt a stance proactive and experimental, turning AI into an ally.

Recommended courses:

AI and entrepreneurship: new market frontiers

Artificial intelligence is not only transforming the traditional job market, it is also paving the way for new business models. Digital entrepreneurs are using AI to create scalable products such as intelligent assistants, recommendation systems, and data-driven SaaS platforms. No-code tools combined with AI agents are enabling the emergence of lean, highly automated, and highly personalized startups.

A great example is the AI-based micro-SaaS, which solve very specific problems and can be created by a single person. Platforms like Bubble, FlutterFlow and Make, integrated with OpenAI models, make this scenario not only possible, but accessible.

For those who wish to explore this new territory, we recommend SaaS IA NoCode Training, designed to transform ideas into digital products using the power of artificial intelligence.

How AI is changing the market and shaping the future

Artificial intelligence is changing the market in an irreversible way. It is not only a technological revolution, but also a social, professional and economic transformation. The question is no longer “if” AI will impact your work, but “how will you position yourself in this new era”.

The good news is that there have never been so many accessible tools for those who want to learn AI in practice.

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