Italian Engineer Successfully Runs a 744-Billion-Parameter AI on a Regular PC in 2026 – Affordable Local AI Solution

Running massive AI models is usually associated with expensive servers, high-end GPUs, and operating costs that are far from budget-friendly. However, in 2026, an Italian engineer demonstrated a different approach: a 744-billion-parameter AI model can apparently run on a regular PC through a local solution called Colibrì. Although its performance is still far from ideal, this achievement opens a new path for AI computing that is more affordable, private, and not entirely dependent on the cloud.

What Is Colibrì and How Does It Work?

Colibrì is experimental software designed to enable extremely large language models to run on home computers. Its main focus is not speed, but proving that inference with massive models is still possible without data center infrastructure.

Colibrì Software for Loading the 1.5 TB GLM-5.2 Model on a Home Computer

One of the most striking things about Colibrì is its ability to load the GLM-5.2 model, which is around 1.5 TB in size. This is clearly too large to fit entirely into the RAM of a regular PC. Because of that, Colibrì uses a staged loading approach and leverages NVMe storage as high-speed virtual memory.

With this method, a home computer does not need hundreds of gigabytes of RAM or a GPU with massive VRAM. The system only retrieves the parts of the model needed as the inference process runs. Technically, this approach does sacrifice speed, but it gives ordinary users a chance to run models that were previously only realistic in data centers.

Mixture-of-Experts (MoE) Architecture as the Key to Efficiency

Another key behind this experiment is the use of the Mixture-of-Experts (MoE) architecture. Unlike regular dense models that activate all parameters for every token, MoE activates only some of the relevant “experts” at each step.

This means that even though the model has a total of 744 billion parameters, not all of them are working at the same time when generating an answer. This is what makes ultra-large models more feasible to run on much simpler hardware. Its efficiency does not mean it is fully lightweight, but it is enough to reduce the computational barrier compared to dense models of equivalent size.

PC Specifications & Performance Challenges Faced

This achievement is interesting, but it is important to understand it realistically: “can run” does not always mean “comfortable to use.” Colibrì is still currently at the proof-of-concept stage.

Minimum Configuration: Standard CPU, 25 GB RAM, and 1 GB/s Virtual NVMe

This experiment is said to run on a relatively affordable configuration: a standard CPU, around 25 GB of RAM, and virtual NVMe storage with a speed of about 1 GB/s. This is far lower than the requirements of conventional AI servers, which usually demand data-center-class GPUs and large amounts of memory.

For many users, those specifications are still fairly reasonable for a modern desktop PC or home workstation. This is where Colibrì becomes appealing: it shifts the idea that massive AI models can only exist on expensive infrastructure.

Extremely Slow Speed (0.05–0.1 Tokens/Second) & No GPU Support Yet

The biggest challenge lies in performance. The reported speed is still extremely slow, at around 0.05–0.1 tokens per second. In practice, this means a single response could take a very long time, especially if the requested answer is fairly long.

In addition, Colibrì is also said not to support GPUs yet. As a result, the entire process depends heavily on the CPU and the mechanism for fetching data from storage. Until major optimizations are made, using it for real-time chatbots is still impractical.

The Prospects of Local AI: Benefits, Privacy, and Cost

Although slow, the idea behind Colibrì has major implications for the future of local AI. Many users do not always need ultra-fast responses, especially if their priorities are privacy, data control, and cost savings.

A Cost-Effective Alternative for Users Concerned About Privacy & Subscription Fees

Local AI offers an important advantage: data does not need to be sent to third-party servers. For users handling sensitive documents, internal research, or personal needs, this approach feels safer and more reassuring.

In addition, local models also have the potential to reduce dependence on monthly subscription fees. If technologies like Colibrì continue to mature, users could have their own AI system at home without having to keep paying for premium cloud access.

Proof-of-Concept Status & Future Optimization Steps

For now, Colibrì is more appropriately viewed as a proof-of-concept than a ready-to-use solution. Its greatest value lies in proving that technical barriers can be overcome with creative approaches, even if the user experience is not yet ideal.

The next optimization steps will likely focus on GPU support, more efficient memory management, faster weight streaming techniques, and adjustments to drastically reduce latency. If these areas continue to develop, it is entirely possible that ultra-large local AI will become more practical in the next few years.

FAQ

Can a 744-billion-parameter AI model run on a regular laptop?

In theory, yes, but it depends heavily on the laptop’s specifications and the software implementation. In the context of Colibrì, “can run” refers more to technical proof than to a comfortable everyday user experience.

How long does it take to get a single answer from Colibrì?

Because its speed is only around 0.05–0.1 tokens per second, a single answer can take a very long time. The longer the requested response, the greater the waiting time.

What is the difference between Mixture-of-Experts architecture and regular AI models?

Regular models generally activate all parameters when processing input. Meanwhile, Mixture-of-Experts activates only some of the relevant “experts,” making it more efficient for extremely large models.

When can Colibrì be used practically for real-time chatbots?

Not anytime soon, based on its current performance. Colibrì will only become more realistic for real-time chatbots after major optimizations, especially in inference speed and GPU support.

Source: https://telset.id/news/ai/insinyur-italia-jalankan-model-ai-744-miliar-parameter-di-pc-biasa

This article was written by artificial intelligence (AI) using the deepseek-v4-pro model via SumoPod AI.

This article was translated by Artificial Intelligence (AI) using gpt-5.4 via SumoPod AI.

Insinyur Italia Sukses Jalankan AI 744 Miliar Parameter di PC Biasa pada 2026 – Solusi AI Lokal Tanpa Mahal

Menjalankan model AI raksasa biasanya identik dengan server mahal, GPU kelas atas, dan biaya operasional yang tidak ramah kantong. Namun pada 2026, seorang insinyur Italia menunjukkan pendekatan berbeda: model AI 744 miliar parameter ternyata bisa dijalankan di PC biasa melalui solusi lokal bernama Colibrì. Meski performanya masih jauh dari ideal, pencapaian ini membuka arah baru bagi komputasi AI yang lebih hemat, privat, dan tidak sepenuhnya bergantung pada cloud.

Apa Itu Colibrì dan Bagaimana Cara Kerjanya?

Colibrì adalah perangkat lunak eksperimental yang dirancang untuk memungkinkan model bahasa berukuran sangat besar berjalan di komputer rumahan. Fokus utamanya bukan kecepatan, melainkan membuktikan bahwa inferensi model raksasa tetap mungkin dilakukan tanpa infrastruktur pusat data.

Perangkat Lunak Colibrì untuk Memuat Model GLM-5.2 1,5 TB di Komputer Rumahan

Salah satu hal paling mencolok dari Colibrì adalah kemampuannya memuat model GLM-5.2 yang berukuran sekitar 1,5 TB. Ukuran ini jelas terlalu besar untuk dimasukkan utuh ke RAM PC biasa. Karena itu, Colibrì memakai pendekatan pemuatan bertahap dan memanfaatkan penyimpanan NVMe sebagai memori virtual berkecepatan tinggi.

Dengan cara ini, komputer rumahan tidak perlu memiliki ratusan gigabita RAM atau GPU VRAM besar. Sistem cukup mengambil bagian model yang dibutuhkan saat proses inferensi berjalan. Secara teknis, pendekatan ini memang mengorbankan kecepatan, tetapi memberi peluang bagi pengguna biasa untuk menjalankan model yang sebelumnya hanya realistis di pusat data.

Arsitektur Mixture-of-Experts (MoE) sebagai Kunci Efisiensi

Kunci lain di balik eksperimen ini adalah penggunaan arsitektur Mixture-of-Experts (MoE). Berbeda dari model dense biasa yang mengaktifkan seluruh parameter untuk setiap token, MoE hanya mengaktifkan sebagian “pakar” yang relevan pada tiap langkah.

Artinya, meskipun total parameter model mencapai 744 miliar, tidak semua parameter bekerja sekaligus saat menghasilkan jawaban. Inilah yang membuat model superbesar lebih mungkin dijalankan di perangkat yang jauh lebih sederhana. Efisiensinya bukan berarti ringan sepenuhnya, tetapi cukup untuk menurunkan hambatan komputasi dibanding model dense dengan ukuran setara.

Spesifikasi PC & Tantangan Kinerja yang Dihadapi

Pencapaian ini menarik, tetapi penting dipahami secara realistis: “bisa dijalankan” tidak selalu berarti “nyaman dipakai”. Colibrì saat ini masih berada pada tahap pembuktian konsep.

Konfigurasi Minimal: CPU Biasa, RAM 25 GB, dan NVMe Virtual 1 GB/s

Eksperimen ini disebut dapat berjalan pada konfigurasi yang relatif terjangkau: CPU biasa, RAM sekitar 25 GB, dan penyimpanan NVMe virtual dengan kecepatan sekitar 1 GB/s. Ini jauh lebih rendah dibanding kebutuhan server AI konvensional yang biasanya menuntut GPU kelas data center dan memori besar.

Bagi banyak pengguna, spesifikasi tersebut masih tergolong masuk akal untuk PC desktop modern atau workstation rumahan. Di sinilah daya tarik Colibrì muncul: ia menggeser ide bahwa model AI raksasa hanya bisa hidup di infrastruktur mahal.

Kecepatan Sangat Lambat (0,05–0,1 Token/Detik) & Belum Mendukung GPU

Tantangan terbesarnya ada pada performa. Kecepatan yang dilaporkan masih sangat lambat, yakni sekitar 0,05–0,1 token per detik. Dalam praktiknya, ini berarti satu respons bisa membutuhkan waktu sangat lama, terutama jika jawaban yang diminta cukup panjang.

Selain itu, Colibrì juga disebut belum mendukung GPU. Akibatnya, seluruh proses sangat bergantung pada CPU dan mekanisme pemanggilan data dari penyimpanan. Selama belum ada optimasi besar, penggunaan untuk chatbot real-time masih belum praktis.

Prospek AI Lokal: Manfaat, Privasi, dan Biaya

Meski lambat, ide di balik Colibrì punya dampak besar untuk masa depan AI lokal. Banyak pengguna sebenarnya tidak selalu membutuhkan respons supercepat, terutama jika prioritas mereka adalah privasi, kontrol data, dan penghematan biaya.

Alternatif Hemat untuk Pengguna yang Khawatir Privasi & Biaya Langganan

AI lokal memberi keuntungan penting: data tidak perlu dikirim ke server pihak ketiga. Untuk pengguna yang menangani dokumen sensitif, riset internal, atau kebutuhan personal, pendekatan ini terasa lebih aman dan menenangkan.

Selain itu, model lokal juga berpotensi mengurangi ketergantungan pada biaya langganan bulanan. Jika teknologi seperti Colibrì makin matang, pengguna bisa memiliki sistem AI sendiri di rumah tanpa harus terus membayar akses cloud premium.

Status Proof-of-Concept & Langkah Optimasi ke Depan

Untuk saat ini, Colibrì masih lebih tepat dipandang sebagai proof-of-concept daripada solusi siap pakai. Nilai terbesarnya ada pada pembuktian bahwa hambatan teknis bisa ditembus dengan pendekatan kreatif, meski belum ideal dari sisi pengalaman pengguna.

Langkah optimasi berikutnya kemungkinan akan berfokus pada dukungan GPU, manajemen memori yang lebih efisien, teknik streaming bobot yang lebih cepat, dan penyesuaian agar latensi turun drastis. Jika area-area ini berkembang, bukan tidak mungkin AI lokal superbesar akan menjadi lebih praktis dalam beberapa tahun ke depan.

FAQ

Apakah model AI 744 miliar parameter bisa dijalankan di laptop biasa?

Secara teori bisa, tetapi sangat bergantung pada spesifikasi laptop dan implementasi perangkat lunaknya. Dalam konteks Colibrì, yang dimaksud “bisa dijalankan” lebih ke pembuktian teknis, bukan pengalaman penggunaan yang nyaman sehari-hari.

Berapa lama waktu yang dibutuhkan untuk mendapatkan satu jawaban dari Colibrì?

Karena kecepatannya hanya sekitar 0,05–0,1 token per detik, satu jawaban bisa memakan waktu sangat lama. Semakin panjang respons yang diminta, semakin besar jeda tunggunya.

Apa bedanya arsitektur Mixture-of-Experts dengan model AI biasa?

Model biasa umumnya mengaktifkan seluruh parameter saat memproses input. Sementara itu, Mixture-of-Experts hanya mengaktifkan sebagian “pakar” yang relevan, sehingga lebih efisien untuk model berukuran sangat besar.

Kapan Colibrì bisa digunakan secara praktis untuk chatbot real-time?

Belum dalam waktu dekat jika melihat performa saat ini. Colibrì baru akan lebih realistis untuk chatbot real-time setelah ada optimasi besar, terutama pada kecepatan inferensi dan dukungan GPU.

Sumber: https://telset.id/news/ai/insinyur-italia-jalankan-model-ai-744-miliar-parameter-di-pc-biasa

Artikel ini ditulis oleh kecerdasan buatan (AI) menggunakan model deepseek-v4-pro via SumoPod AI.

Revealed! How to Trigger Erling Haaland’s Viking Row Animation Easter Egg on Google (2026)

Google has once again delivered a small surprise that has football fans buzzing with curiosity. This time, the spotlight is on Erling Haaland through the “Viking Row” animation Easter egg in Google search results. Hidden features like this may be simple, but their impact is huge: fun, interactive, and quick to go viral on social media.

For Haaland fans or users who love hunting for unique features in Google Search, this animation is definitely one worth trying. Here’s a complete explanation of what the Viking Row animation is, how to trigger it, and why this feature is getting so much attention.

What Is Google’s Viking Row Animation for Erling Haaland?

Google’s Viking Row animation for Erling Haaland is an interactive Easter egg that appears when users search for the striker’s name on Google. Once triggered, the screen displays a visual effect themed around a signature celebration closely associated with Haaland’s image and Viking-inspired vibe.

The Easter Egg Phenomenon in Google Search

Google has long been known for slipping Easter eggs into its search engine. An Easter egg is a hidden feature, visual effect, or small interaction usually created to celebrate popular figures, cultural moments, or certain achievements.

Several previous Google Easter eggs also went viral because they were easy to try and offered an experience different from a typical search. Haaland’s animation reinforces Google’s tradition of blending technology, entertainment, and pop culture into one lighthearted experience.

Interactive Animation Details

When this animation is activated, users will see visual elements pointing to the “Viking Row,” a celebration closely tied to Haaland’s identity. The effect is designed to be brief, eye-catching, and instantly feel like a digital tribute to the player.

Animation illustration:

Animations like this are usually designed to run smoothly on the search page without requiring users to open any additional apps or websites. In fact, it’s this very simplicity that makes them so quick to capture attention.

How to Trigger the Viking Row Animation in Google Search

To see this Easter egg, users only need to follow a few simple steps. No special app or complicated settings are required.

Easy Steps

1. Open Google Search through your browser or the Google app.
2. Type the keyword: Erling Haaland.
3. Go to the official search results page for that name.
4. Look for an icon or interactive element that appears in the information panel or search results area.
5. Tap or click that element to trigger the Viking Row animation.

If the feature is currently active globally, the animation will usually appear within seconds after the interaction. On some devices, users may need to refresh the page or try a different browser.

Tips to Make the Animation Appear Properly

To make the animation easier to access, make sure you’re using the latest version of your browser or the Google app. In addition, a stable internet connection helps the interactive element load properly.

If it still doesn’t appear, try using a more specific keyword such as Erling Haaland Google or repeat the search a little later. Sometimes features like this are rolled out gradually, so they may not be immediately available to all users at the same time.

Why Did Google Create a Special Animation for Haaland?

Google usually doesn’t choose figures for Easter eggs at random. Haaland’s presence in this feature shows that he has a major impact, both on the pitch and in the digital space.

Recognition of Outstanding Performance

Erling Haaland is known as one of the most prominent strikers of the modern football era. His clinical finishing, consistent performances, and global popularity make his name highly relevant to be celebrated through a special feature.

This animation can be seen as a form of appreciation for his achievements and influence. Google often captures moments when an athlete is at the peak of public attention, then turns that moment into an interactive experience that anyone can easily access.

A Unique Form of Interaction

Beyond serving as a tribute, Easter eggs like this are also a way for Google to make search feel more alive. Users don’t just get information, but also a small, enjoyable experience.

This kind of unique interaction helps Google stay closely connected to digital culture trends. On the other hand, users feel more engaged because there’s an element of surprise when searching for their favorite figures.

User Experience and Viral Impact

One reason Google Easter eggs often become widely discussed is that the format is incredibly easy to share. Once someone discovers it, others immediately want to try it too.

Fan Reactions on Social Media

Football fans and Haaland supporters were quick to spread this discovery on social media. Many shared screenshots, screen recordings, and spontaneous reactions when the animation appeared on their devices.

Its viral effect comes from a combination of three things: Haaland’s star power, a hidden feature from Google, and public curiosity. Content like this is perfect for short-form platforms such as X, TikTok, Instagram Reels, and Threads.

The Popularity of Hidden Features

Hidden features always have a special appeal because they create a sense of exclusivity. Even though they’re actually easy to access, Easter eggs still feel special because not everyone notices them right away.

Their popularity also shows that users enjoy digital experiences that are brief but memorable. In this context, the Viking Row animation is not just a gimmick, but part of an effective engagement strategy.

FAQ

How can I see the Viking Row animation on Google?

Search for Erling Haaland on Google, then check whether there is an interactive element in the search results. If it’s available, click or tap that element to display the animation.

Is this animation available on all devices?

Not always. Features like this are usually available on many devices, but their appearance may vary depending on region, app version, browser, or system updates.

How long will this animation be available?

Google rarely gives a specific timeframe for Easter eggs like this. It may remain available for quite a while, but it could also be removed or limited after a certain period.

Are there other players who have received a similar Easter egg?

Possibly, since Google has created special features for popular figures from various fields before. However, not every athlete or football player gets an animation in the same format.

Source: https://share.google/YFAhOmYx81v1VlSF7

This article was written by artificial intelligence (AI) using the deepseek-v4-pro model via SumoPod AI.

This article was translated by Artificial Intelligence (AI) using gpt-5.4 via SumoPod AI.

Terkuak! Begini Cara Memicu Easter Egg Animasi Viking Row Erling Haaland di Google (2026)

Google kembali menghadirkan kejutan kecil yang sukses bikin penggemar sepak bola penasaran. Kali ini, sorotan tertuju pada Erling Haaland lewat Easter egg animasi “Viking Row” di hasil pencarian Google. Fitur tersembunyi seperti ini memang sederhana, tetapi efeknya besar: seru, interaktif, dan cepat viral di media sosial.

Bagi fans Haaland atau pengguna yang gemar berburu fitur unik di Google Search, animasi ini jadi salah satu hal yang wajib dicoba. Berikut penjelasan lengkap tentang apa itu animasi Viking Row, cara memicunya, dan alasan mengapa fitur ini ramai dibicarakan.

Apa Itu Animasi Viking Row Google untuk Erling Haaland?

Animasi Viking Row Google untuk Erling Haaland adalah Easter egg interaktif yang muncul saat pengguna mencari nama sang striker di Google. Begitu dipicu, layar akan menampilkan efek visual bertema selebrasi khas yang identik dengan citra Haaland dan nuansa Viking.

Fenomena Easter Egg di Google Search

Google sudah lama dikenal gemar menyisipkan Easter egg di mesin pencarinya. Easter egg adalah fitur tersembunyi, efek visual, atau interaksi kecil yang biasanya dibuat untuk merayakan tokoh populer, momen budaya, atau pencapaian tertentu.

Beberapa Easter egg Google sebelumnya juga sempat viral karena mudah dicoba dan memberi pengalaman yang berbeda dari pencarian biasa. Kehadiran animasi Haaland memperkuat tradisi Google dalam memadukan teknologi, hiburan, dan budaya pop dalam satu pengalaman ringan.

Detail Animasi Interaktif

Saat animasi ini aktif, pengguna akan melihat elemen visual yang mengarah pada “Viking Row”, selebrasi yang lekat dengan identitas Haaland. Efeknya dibuat singkat, atraktif, dan langsung terasa seperti penghormatan digital untuk sang pemain.

Ilustrasi animasi:

Animasi seperti ini biasanya dirancang agar tetap ringan dijalankan di halaman pencarian, tanpa membuat pengguna perlu membuka aplikasi atau situs tambahan. Justru kesederhanaan inilah yang membuatnya cepat menarik perhatian.

Cara Memicu Animasi Viking Row di Pencarian Google

Untuk melihat Easter egg ini, pengguna cukup melakukan beberapa langkah sederhana. Tidak perlu aplikasi khusus atau pengaturan rumit.

Langkah-Langkah Mudah

1. Buka Google Search melalui browser atau aplikasi Google.
2. Ketik kata kunci: Erling Haaland.
3. Masuk ke halaman hasil pencarian resmi untuk nama tersebut.
4. Cari ikon atau elemen interaktif yang muncul di panel informasi atau area hasil pencarian.
5. Ketuk atau klik elemen tersebut untuk memicu animasi Viking Row.

Jika fitur sedang aktif secara global, animasi biasanya akan muncul dalam hitungan detik setelah interaksi dilakukan. Pada beberapa perangkat, pengguna mungkin perlu me-refresh halaman atau mencoba lewat browser lain.

Tips agar Animasi Muncul Maksimal

Agar animasi lebih mudah muncul, pastikan Anda menggunakan versi browser atau aplikasi Google yang terbaru. Selain itu, koneksi internet yang stabil membantu elemen interaktif dimuat dengan sempurna.

Jika belum muncul, coba gunakan kata kunci yang lebih spesifik seperti Erling Haaland Google atau ulangi pencarian beberapa saat kemudian. Kadang fitur seperti ini dirilis bertahap, sehingga tidak langsung tersedia untuk semua pengguna di waktu yang sama.

Mengapa Google Membuat Animasi Khusus Haaland?

Google biasanya tidak asal memilih figur untuk dijadikan Easter egg. Kehadiran Haaland dalam fitur ini menunjukkan bahwa ia punya dampak besar, baik di lapangan maupun di ruang digital.

Apresiasi Performa Gemilang

Erling Haaland dikenal sebagai salah satu striker paling menonjol dalam era sepak bola modern. Ketajamannya di depan gawang, konsistensi performa, dan popularitas global membuat namanya sangat relevan untuk dirayakan lewat fitur khusus.

Animasi ini bisa dilihat sebagai bentuk apresiasi atas pencapaian dan pengaruhnya. Google kerap menangkap momen ketika seorang atlet sedang berada di puncak sorotan publik, lalu mengubahnya menjadi pengalaman interaktif yang mudah diakses semua orang.

Bentuk Interaksi Unik

Selain sebagai penghormatan, Easter egg seperti ini juga menjadi cara Google membuat pencarian terasa lebih hidup. Pengguna tidak hanya mendapatkan informasi, tetapi juga pengalaman kecil yang menyenangkan.

Interaksi unik semacam ini membantu Google tetap dekat dengan tren budaya digital. Di sisi lain, pengguna merasa lebih terlibat karena ada unsur kejutan saat mencari tokoh favorit mereka.

Pengalaman Pengguna dan Dampak Viral

Salah satu alasan Easter egg Google sering ramai dibicarakan adalah karena formatnya sangat mudah dibagikan. Begitu seseorang menemukannya, orang lain langsung ingin ikut mencoba.

Respons Penggemar di Media Sosial

Penggemar sepak bola dan fans Haaland cepat menyebarkan temuan ini di media sosial. Banyak yang membagikan tangkapan layar, rekaman layar, hingga reaksi spontan saat animasi muncul di perangkat mereka.

Efek viralnya muncul karena kombinasi tiga hal: nama besar Haaland, fitur tersembunyi dari Google, dan rasa penasaran publik. Konten seperti ini sangat cocok untuk platform pendek seperti X, TikTok, Instagram Reels, dan Threads.

Popularitas Fitur Tersembunyi

Fitur tersembunyi selalu punya daya tarik tersendiri karena memberi kesan eksklusif. Meski sebenarnya mudah diakses, Easter egg tetap terasa spesial karena tidak semua orang langsung menyadarinya.

Popularitasnya juga menunjukkan bahwa pengguna menyukai pengalaman digital yang singkat tetapi berkesan. Dalam konteks ini, animasi Viking Row bukan sekadar gimmick, melainkan bagian dari strategi engagement yang efektif.

FAQ

Bagaimana cara melihat animasi Viking Row di Google?

Cari nama Erling Haaland di Google, lalu perhatikan apakah ada elemen interaktif di hasil pencarian. Jika tersedia, klik atau ketuk elemen tersebut untuk memunculkan animasinya.

Apakah animasi ini tersedia di semua perangkat?

Tidak selalu. Biasanya fitur seperti ini tersedia di banyak perangkat, tetapi kemunculannya bisa berbeda tergantung wilayah, versi aplikasi, browser, atau pembaruan sistem.

Berapa lama animasi ini akan tersedia?

Google jarang memberi durasi pasti untuk Easter egg semacam ini. Bisa bertahan cukup lama, tetapi bisa juga dihapus atau dibatasi setelah periode tertentu.

Apakah ada pemain lain yang mendapat Easter egg serupa?

Ada kemungkinan, karena Google pernah membuat fitur khusus untuk tokoh populer dari berbagai bidang. Namun, tidak semua atlet atau pemain sepak bola mendapat animasi dengan format yang sama.

Sumber: https://share.google/YFAhOmYx81v1VlSF7

Artikel ini ditulis oleh kecerdasan buatan (AI) menggunakan model deepseek-v4-pro via SumoPod AI.

7 Modern Malware Threats to macOS in 2026: How Fake Apps Work & Tips to Protect Yourself

macOS has long been known as being more secure than many other operating systems. However, in 2026, that assumption is increasingly being exploited by cybercriminals. They do not always attack using complex techniques, but rather through fake apps, counterfeit installers, pirated downloads, and convincing-looking links.

The problem is that modern attacks on Mac are no longer easy to recognize. Many types of malware are designed to look like normal applications, request permissions in ways that appear legitimate, and then quietly access important data. That is why macOS users need to understand attack patterns, rather than simply relying on the reputation of Apple devices.

Why Is macOS Malware Becoming More Dangerous in 2026?

A shift in targets from Windows to macOS

In the past, Windows was the primary target because of its large market share. Today, macOS has also become a target because its user base continues to grow, especially among professionals, businesspeople, creators, and remote work teams. To attackers, Mac devices are often seen as storing high-value data such as work documents, cloud credentials, financial data, and business account access.

There is also a psychological factor that benefits attackers: many Mac users feel their devices are “secure enough” by default. This overconfidence often makes people careless when downloading apps from unofficial sources, opening files of unclear origin, or ignoring system warning signs.

Fake app disguise techniques that are difficult to detect

Modern malware rarely appears as a suspicious file with a strange name. Instead, it disguises itself as productivity apps, system cleaning utilities, free VPNs, editing tools, cracked software, or fake updates for browsers and media players.

Installer interfaces are also becoming more convincing. Icons are made to look professional, app names resemble popular brands, and the download sites look like official pages. In some cases, attackers imitate the macOS installation flow so neatly that users do not realize they are granting access to malicious software.

How Modern Malware Works: Infection Through Fake Apps

The infiltration process through pirated or imitation apps

One of the most common infection routes is pirated apps or imitation versions of popular software. Users typically look for free versions of paid apps, then download a .dmg file or installer from an unofficial site. That is where the malware gets in.

The scheme often looks like this:

1. The user downloads an app from a third-party website.
2. The installer requests extra steps such as disabling certain protections or manually moving the app.
3. The app appears to run normally, but in the background it plants additional components.
4. Those components may be tasked with stealing passwords, monitoring activity, installing a backdoor, or downloading other malware.

This attack model is effective because the victim feels they are indeed installing the app they wanted. As a result, the malicious activity appears to be a normal part of the installation process.

Exploitation of system permissions and access to sensitive data

In macOS, many important functions are protected by a permissions system. However, modern malware does not always “break through” those protections head-on. It often manipulates users into granting permissions themselves, such as access to the Downloads folder, Documents, Accessibility, Screen Recording, or Full Disk Access.

Once permission is granted, the risk increases dramatically. Malware can:

• Read sensitive files
• Steal saved login data
• Record screen activity
• Monitor the clipboard
• Access browser session tokens or work app tokens
• Abuse accounts that are currently logged in

In more advanced attacks, malware can also persist after a restart and continue running without obvious symptoms. Users often only realize it when their accounts are compromised, files are encrypted, or the device starts behaving abnormally.

Main Attack Vectors to Watch Out For

Downloads from unofficial sites and phishing links

Most infections do not begin with a “major hack,” but with a small decision: click a link, download a file, then install it. Unofficial sites often offer free premium software, fake emergency updates, or tools that supposedly are required to open certain documents.

Phishing links are also becoming more polished. Emails or messages can impersonate software vendors, cloud services, and even Apple security notifications. When victims are directed to a fake page, they are asked to download a “verification app,” “security update,” or “supporting driver” that is actually malware.

Warning signs to be suspicious of:

• The site domain looks similar, but it is not the official domain
• There is a sense of urgency such as “your account will be blocked”
• The file is downloaded from a page full of ads or redirects
• The app asks you to bypass security without a clear reason
• The developer name is inconsistent with the app’s brand

Fileless malware using legitimate scripts

Another threat that is becoming increasingly relevant is fileless malware. This type does not always depend on traditional malicious files that are easy to scan. It can exploit legitimate scripts and built-in system components to execute commands, retrieve payloads, or maintain access.

This approach is dangerous because its activity appears to be a normal process. Attackers can use script interpreters, system automation, or tasks that look legitimate to carry out harmful actions. As a result, detection becomes more difficult, especially if users rarely check system activity or security logs.

For everyday users, the key point is simple: modern threats do not always come in the form of a clearly suspicious app. Sometimes, the attack runs through processes that appear “official.”

Effective Protection Strategies for macOS Users

Basic security practices: only download from the App Store & verify the developer

The most effective protective step is actually the most basic one: download apps only from the App Store or the developer’s official website. If you must install from outside the App Store, make sure the developer name, website domain, reviews, and reputation are truly valid.

Some important safe habits:

• Avoid pirated software, cracks, and keygens
• Do not install apps from random links in emails, chats, or forums
• Check whether the app is genuinely necessary
• Be wary of permission requests that feel excessive
• Do not ignore security warnings from macOS

If a simple note-taking app suddenly asks for Screen Recording, Accessibility, or Full Disk Access, that should raise questions. The principle is: permissions should be proportional to the app’s function.

Additional security tools: XProtect, system updates, and firewall

macOS already has built-in security layers such as XProtect, Gatekeeper, and security update mechanisms. These features help block known malware, verify app authenticity, and close vulnerabilities that could be exploited.

To keep protection effective:

• Always enable automatic system updates
• Do not delay security updates
• Use the built-in macOS firewall
• Review the Login Items list and background processes regularly
• Remove apps that are no longer used
• Use a password manager and two-factor authentication for important accounts

For users with higher risk, such as remote workers, business teams, or people who frequently download many tools, additional third-party security solutions can help. However, the foundation remains the same: safe download sources, a system that is always updated, and disciplined digital habits.

Conclusion

Malware threats on macOS in 2026 are no longer a side issue. The focus of attacks has shifted to subtler techniques: fake apps, abused system permissions, phishing, and fileless malware that is hard to spot. This means protection is no longer sufficient if it relies only on Apple’s strong brand name or the assumption that Macs are “safer.”

The safest users are usually not the most technical ones, but the most careful ones. As long as you only download from trusted sources, check app permissions, update your system regularly, and stay alert to suspicious links, the risk of infection can be reduced significantly.

FAQ

What is the difference between macOS malware and Windows malware?

In terms of purpose, both are designed to steal data, take over access, or damage systems. The difference is that macOS malware is often designed to blend in more neatly within the Apple ecosystem and exploit Mac users’ sense of security.

Can a Mac get malware through Safari?

Yes. Safari itself is not the main cause, but the browser can become an entry point when users open malicious websites, click phishing links, or download files from untrusted sources.

How can you identify a fake app on Mac?

Check the download source, developer name, domain appearance, and the permissions requested by the app. If the app asks for irrelevant access or requires you to bypass security warnings, it is best not to continue.

Is third-party antivirus necessary for macOS?

Not always for everyone, because macOS already includes built-in protections. However, for high-risk users or those who frequently install apps from outside the App Store, additional antivirus can serve as an extra layer of security.

Sources

This article was written by artificial intelligence (AI) using the deepseek-v4-pro model via SumoPod AI.

This article was translated by Artificial Intelligence (AI) using gpt-5.4 via SumoPod AI.

7 Ancaman Malware Modern MacOS 2026: Cara Kerja Aplikasi Palsu & Tips Melindungi Mac Anda

Mac memang dikenal lebih ketat dalam urusan keamanan, tetapi itu bukan berarti kebal. Di 2026, ancaman malware MacOS berkembang jauh lebih canggih: pelaku tidak lagi hanya mengandalkan file mencurigakan, melainkan menyamarkan serangan lewat aplikasi palsu, pembaruan palsu, hingga file installer yang terlihat meyakinkan. Akibatnya, pengguna bisa tertipu tanpa sadar dan memberikan akses ke data penting mereka sendiri.

Artikel ini membahas bagaimana malware modern menyerang Mac, cara aplikasi palsu bekerja, serta langkah praktis untuk memperkuat perlindungan perangkat Anda.

Mengapa Malware MacOS Semakin Berbahaya di 2026?

Pertumbuhan pengguna Mac yang terus meningkat membuat ekosistem Apple menjadi target yang semakin menarik. Penyerang tahu bahwa banyak pengguna masih berasumsi Mac lebih aman secara default, sehingga kewaspadaan sering kali lebih rendah dibanding pengguna platform lain.

Evolusi Serangan dari Spyware ke Ransomware

Dulu, ancaman pada Mac lebih sering berupa adware, spyware, atau aplikasi pengganggu yang menampilkan iklan berlebihan. Kini, serangannya jauh lebih serius. Malware modern mampu mencuri file, merekam aktivitas pengguna, membajak sesi login, hingga mengenkripsi data dan meminta tebusan.

Perubahan ini menunjukkan bahwa penyerang tidak lagi sekadar mencari gangguan kecil, tetapi keuntungan finansial langsung. Mereka membangun malware yang modular: satu komponen membuka jalan, komponen lain mengumpulkan data, dan tahap berikutnya bisa mengeksekusi pemerasan atau pencurian akun.

Target Utama: Data Pribadi dan Kredensial Login

Target paling bernilai di MacOS saat ini adalah data pribadi dan kredensial. Ini termasuk password tersimpan, token sesi browser, dokumen kerja, file cloud sync, data dompet kripto, hingga akses ke email dan akun bisnis.

Begitu kredensial dicuri, dampaknya bisa meluas ke banyak layanan sekaligus. Satu akun email yang dibajak dapat dipakai untuk reset password layanan lain, membuka akses ke penyimpanan cloud, bahkan menjadi pintu masuk ke sistem kantor.

Teknik Penyamaran Aplikasi Palsu yang Digunakan Malware Modern

Salah satu trik paling efektif di 2026 adalah penyamaran. Malware tidak selalu datang sebagai file bernama aneh. Justru banyak yang dibungkus dalam aplikasi yang tampak profesional dan familier.

Kode Berbahaya yang Disembunyikan di Aplikasi Palsu Populer

Penyerang sering meniru aplikasi yang banyak dicari: browser alternatif, editor PDF, alat meeting, utilitas pembersih sistem, software desain, hingga aplikasi AI. Tampilan situs unduhannya dibuat rapi, nama file installernya wajar, dan ikon aplikasinya dibuat semirip mungkin dengan versi asli.

Di balik tampilannya, aplikasi palsu ini bisa membawa kode berbahaya yang aktif setelah instalasi. Ada yang langsung berjalan saat aplikasi dibuka, ada juga yang menunggu izin tertentu diberikan lebih dulu. Beberapa malware bahkan menyisipkan fungsi jahat ke dalam aplikasi yang tampak bekerja normal, sehingga korban tidak langsung curiga.

Eksploitasi Izin Sistem dan Pengguna yang Tidak Sadar

MacOS memiliki sistem izin yang cukup ketat, tetapi justru di sinilah penyerang memainkan rekayasa sosial. Pengguna dibujuk untuk memberi akses ke folder Downloads, Documents, Accessibility, Screen Recording, atau Full Disk Access dengan alasan fitur aplikasi tidak akan berjalan tanpa izin tersebut.

Ketika izin sensitif diberikan, malware bisa mengamati aktivitas pengguna, membaca file penting, mengambil screenshot, atau memantau input tertentu. Dalam banyak kasus, serangan berhasil bukan karena celah teknis yang rumit, tetapi karena korban percaya aplikasi tersebut sah.

Cara Kerja Malware Modern: Tahapan Infeksi dan Eksekusi

Untuk memahami risikonya, penting melihat bagaimana serangan biasanya berlangsung dari awal sampai akhir. Malware modern jarang bekerja secara kasar; ia bergerak bertahap agar tidak mudah terdeteksi.

Infeksi Awal Lewat Unduhan, Email, atau Iklan Berbahaya

Tahap awal infeksi umumnya terjadi melalui tiga jalur utama:

• Unduhan dari situs tidak resmi atau hasil pencarian palsu
• Lampiran email yang menyamar sebagai invoice, dokumen kerja, atau pembaruan akun
• Iklan berbahaya yang mengarahkan pengguna ke halaman unduhan palsu

Beberapa kampanye juga memanfaatkan pesan pop-up seperti “Mac Anda terinfeksi”, “codec perlu diperbarui”, atau “versi aplikasi Anda sudah usang”. Saat pengguna mengklik dan menginstal file tersebut, proses infeksi dimulai.

Pada tahap ini, malware bisa:

• Menyalin dirinya ke direktori sistem atau pengguna
• Menjalankan skrip tambahan dari server jarak jauh
• Mengunduh muatan lanjutan sesuai profil korban
• Memeriksa apakah perangkat berjalan di lingkungan analisis agar bisa menghindari deteksi

Teknik Persistensi dan Pengumpulan Data Tanpa Deteksi

Setelah aktif, malware berusaha bertahan selama mungkin. Teknik persistensi di Mac dapat melibatkan item login, launch agents, launch daemons, profil konfigurasi palsu, atau proses latar belakang yang menyamar sebagai komponen normal.

Setelah bertahan, malware mulai mengumpulkan data secara diam-diam. Data yang sering diburu meliputi:

• Password yang tersimpan di browser
• Cookie dan token sesi login
• Riwayat penelusuran
• Dokumen lokal dan file sinkronisasi cloud
• Informasi perangkat dan jaringan
• Data clipboard, termasuk alamat wallet atau kode OTP yang disalin pengguna

Yang membuatnya berbahaya, aktivitas ini sering dilakukan perlahan agar tidak memicu kecurigaan. Pengguna tetap bisa memakai Mac seperti biasa, sementara data penting sudah diekstrak sedikit demi sedikit.

Strategi Perlindungan MacOS 2026 dari Ancaman Modern

Kabar baiknya, banyak serangan bisa dicegah dengan disiplin keamanan dasar yang konsisten. Perlindungan terbaik bukan hanya mengandalkan satu alat, tetapi kombinasi kebiasaan aman dan pengaturan sistem yang tepat.

Praktik Verifikasi Aplikasi dan Sumber Unduhan

Sebelum menginstal aplikasi apa pun, pastikan sumber unduhannya benar-benar resmi. Hindari mengunduh dari situs mirror acak, forum tidak jelas, atau iklan hasil pencarian yang meniru situs asli.

Lakukan langkah verifikasi berikut:

• Unduh aplikasi hanya dari Mac App Store atau situs resmi vendor
• Periksa ejaan domain dengan teliti
• Waspadai aplikasi “gratis” untuk software berbayar populer
• Cek apakah pengembang memiliki reputasi dan jejak digital yang jelas
• Jangan terburu-buru memberi izin sistem sensitif tanpa memahami fungsinya

Jika sebuah aplikasi meminta akses yang terasa tidak relevan, itu tanda bahaya. Misalnya, aplikasi PDF sederhana seharusnya tidak perlu Screen Recording atau Accessibility kecuali ada alasan yang sangat spesifik.

Pengaturan Keamanan Sistem dan Alat Deteksi Terkini

Selain berhati-hati saat menginstal aplikasi, pastikan pertahanan bawaan Mac tetap optimal. Update sistem secara rutin penting karena banyak malware memanfaatkan perangkat yang terlambat menerima patch keamanan.

Langkah perlindungan yang disarankan:

• Aktifkan pembaruan otomatis MacOS dan aplikasi
• Gunakan Gatekeeper dan jangan menonaktifkannya sembarangan
• Tinjau izin aplikasi secara berkala di System Settings
• Aktifkan FileVault untuk melindungi data jika perangkat hilang
• Gunakan password manager dan autentikasi dua faktor
• Cadangkan data secara rutin agar siap jika terjadi ransomware
• Pertimbangkan alat keamanan tambahan yang mampu mendeteksi perilaku mencurigakan, bukan hanya signature lama

Di 2026, solusi keamanan yang baik bukan sekadar antivirus tradisional. Idealnya, alat tersebut mampu memantau perubahan persistensi, perilaku aplikasi, koneksi keluar yang aneh, dan upaya akses ke data sensitif.

FAQ

Apakah Mac benar-benar kebal terhadap malware?

Tidak. Mac memiliki lapisan keamanan yang kuat, tetapi tetap bisa terinfeksi jika pengguna mengunduh aplikasi palsu, memberi izin berlebihan, atau mengabaikan pembaruan sistem. Ancaman modern justru banyak memanfaatkan kelengahan pengguna.

Bagaimana cara membedakan aplikasi asli dan palsu di Mac?

Periksa sumber unduhan, nama domain, identitas pengembang, serta jenis izin yang diminta aplikasi. Jika tampilannya meyakinkan tetapi meminta akses yang tidak relevan atau berasal dari situs tidak resmi, sebaiknya jangan diinstal.

Apa yang harus dilakukan jika Mac terinfeksi malware?

Segera putuskan koneksi internet, hentikan penggunaan akun penting di perangkat tersebut, lalu hapus aplikasi mencurigakan dan lakukan pemindaian keamanan. Setelah itu, ganti password akun penting dari perangkat yang bersih dan periksa izin serta item login yang tidak dikenal.

Apakah antivirus pihak ketiga diperlukan untuk Mac di 2026?

Tidak selalu wajib untuk semua pengguna, tetapi sangat membantu, terutama jika Anda sering mengunduh aplikasi di luar App Store atau menangani data sensitif. Pilih solusi yang fokus pada deteksi perilaku, perlindungan real-time, dan pemantauan persistensi.

Artikel ini ditulis oleh kecerdasan buatan (AI) menggunakan model deepseek-v4-pro via SumoPod AI.

2026: Gemini AI Turns Google Maps Into an Automated Assistant – Restaurant Booking & Touch-Free Navigation

Google Maps is expected to enter a new phase in 2026: no longer just a map app, but an automated assistant capable of understanding context, making suggestions, and then executing them directly. With Gemini AI integration, the experience of finding places, booking restaurants, and even leaving at the right time could happen almost entirely hands-free.

This shift matters because user needs are changing as well. People no longer just want to know the fastest route; they also want help making real-time decisions: when to leave, which restaurant still has availability, whether the weather will disrupt the trip, and how to align everything with their daily schedule.

What Is Gemini AI and How It Integrates with Google Maps

Gemini AI is Google’s multimodal artificial intelligence model designed to understand text, voice, visual context, and real-time data simultaneously. When integrated into Google Maps, Gemini has the potential to transform digital maps into a more active, personalized, and responsive companion system.

Instead of waiting for one command at a time, Maps with Gemini can infer user intent from habits, schedules, locations, and travel preferences. As a result, interactions become more natural: you simply state your destination or need, and the system prepares the steps for you.

Gemini’s role in processing real-time data

Gemini’s main strength lies in its ability to process many signals at once. For example, traffic data, business hours, weather conditions, location crowd levels, calendar changes, and the user’s personal preferences.

With this real-time processing, Google Maps does more than just display information—it can also make more relevant decisions. If a restaurant is fully booked, Gemini can immediately suggest similar options nearby. If a main road is congested due to a local event, the system can adjust the route before you even ask.

New automation: from recommendations to execution

Until now, map apps have generally stopped at the recommendation stage. Gemini pushes Maps to the next level: execution. That means after making a suggestion, the system can also help complete actions such as reservations, ticket bookings, or stopover planning.

This approach makes the user experience far more streamlined. You no longer need to jump between apps just to complete a single travel plan. From searching for a place to confirming an action, everything can happen within one flow.

Key Features: Automatic Booking and Predictive Navigation

Gemini integration opens the door to features that feel highly practical in everyday life. Two of the most notable are automatic booking and predictive navigation that adapts to user activities.

These features are not just cosmetic additions. Their value lies in saving time, reducing distractions while traveling, and enabling the system to act before users feel the need to open another app.

Book tables, tickets, and services without opening another app

Imagine you are looking for a restaurant for dinner. After choosing a place, Gemini-powered Google Maps can immediately check table availability, match it with the number of guests, arrival time, and even seating preferences if supported by service partners.

A similar concept could also be applied to event tickets, salon bookings, auto repair reservations, or other local services. Users simply state their needs, and Gemini handles the process behind the scenes. This turns Maps into an action hub, not just a location search tool.

Smart routes that adapt to your daily schedule

Predictive navigation means routes are no longer calculated statically from point A to point B. The system will consider your calendar, meeting times, pickup locations, break habits, and the likelihood of delays.

If you have a 9:00 a.m. meeting, want to stop briefly for coffee, and then need to pick up your child in the afternoon, Maps can arrange a more logical travel sequence. It can even suggest the ideal departure time based on historical traffic patterns and current conditions.

How Gemini AI Improves Everyday Travel Efficiency

The greatest value of Gemini-powered Maps may actually be felt in the small things that repeat every day. Not just during vacations or long-distance trips, but when you commute to work, meet clients, or organize family schedules.

Efficiency here is not just about arriving faster. It is also about reducing exhausting micro-decisions, minimizing delays, and keeping your daily rhythm running smoothly.

Accurate traffic predictions with personal context

Traffic predictions become more useful when combined with personal context. For two people heading to the same area, the best recommendation may not be the same. One person may need the fastest route, while another may prefer a more stable route with a lower risk of delay.

Gemini can learn these patterns from user habits. If you tend to avoid certain toll roads, prefer parking near the entrance, or often stop at specific points, the system can factor that in when suggesting trips. This is what makes predictions feel more attuned to real needs, not just numbers on a map.

Proactive notifications: leave on time, weather, and events

Proactive notifications are the part that feels most like a personal assistant. The system can remind you to leave earlier because of rain, alert you to a concert causing congestion near your destination, or suggest a route change because parking is expected to be full.

This approach helps users act before problems happen, rather than simply reacting once they are already late. In practice, features like this are highly relevant for urban workers, parents, field business operators, and anyone who depends on daily mobility.

The Future of Life Automation in 2026: Gemini Maps Integrated with Smart Homes

If this integration fully develops, Google Maps will not stand alone. It will become part of an automated ecosystem connected to calendars, smart home devices, vehicles, and other digital services.

That means a trip no longer begins when you open Maps. The system could prepare many things even before you leave home, based on your schedule and environmental conditions.

Synchronization with calendars and IoT devices

With calendar synchronization, Gemini Maps can read your daily agenda and automatically prepare travel reminders. If you have a lunch appointment, the system can suggest when to leave, book a table, and then activate navigation when the time comes.

When connected to IoT devices, the scenario becomes even broader. For example, the home AC turns off automatically when you leave, the porch lights switch on when you are expected to return late, or the car prepares the route as soon as the engine starts. Integrations like these make the experience feel seamless from home to the road and back again.

The potential for premium subscriptions for advanced features

While some features will likely be available for free, it is entirely possible that Google will offer premium plans for more advanced capabilities. For example, cross-service automation, ultra-personalized recommendations, business integrations, or priority access to certain reservation features.

A subscription model like this makes sense if the added value is truly noticeable. Casual users may be satisfied with basic features, while mobile professionals, busy families, or business owners may see major benefits from deeper automation.

FAQ

Is Gemini AI in Google Maps free to use?

Most likely, basic features will be available for free, as with Maps services in general. However, advanced automation features or premium integrations may be offered under a paid model.

How do I enable the automatic booking feature?

If this feature is released, activation will likely be done through Google account settings or the AI features menu in Google Maps. Users will typically need to grant access to their calendar, preferences, and relevant partner services.

When will Gemini AI be available in Indonesia?

There is still no official certainty for all features and regions. Google usually rolls out features in stages, so Indonesia will likely gain access after major markets or through limited trials first.

Can Gemini AI learn my routine without sacrificing privacy?

Ideally, yes—if Google provides transparent privacy controls and clear data management options. Users should still review permissions, location history, and personal preferences to ensure convenience does not come at the expense of control over their data.

This article was written by artificial intelligence (AI) using the deepseek-v4-pro model via SumoPod AI.

This article was translated by Artificial Intelligence (AI) using gpt-5.4 via SumoPod AI.