Xiaomi 17 Ultra
HPE (1/1.4", 200MP) periscope and new lens group
Engineering prototype with a minimum aperture of F3.0± and a maximum aperture of F2.3± within the variable focal length range
Let's analyze based on the available information
The Xiaomi 15 Ultra uses a 1/1.4" HP9 sensor at 100 mm (4.3×) with f/2.6. Since the Xiaomi 17 Ultra will use the same-sized 1/1.4" HPE sensor, we can use the 15 Ultra’s f/2.6 at 100mm as a reference—aperture scales proportionally with focal length
The ratio between f/3.0 and f/2.6 is 3 ÷ 2.6 ≈ 1.15
New focal length: 100 mm × 1.15 = 115 mm
Xiaomi 15 Ultra: f/2.6 @ 100 mm
Xiaomi 17 Ultra (long end): f/3.0 at 115 mm
The ratio between f/3.0 and f/2.3 is 3 ÷ 2.3 ≈ 1.30
Short end focal length: 115 mm ÷ 1.30 ≈ 88 mm (DCS gave approximate f-numbers, so round to 85 mm)
Thus, the Xiaomi 17 Ultra periscope should span roughly 85mm (3.7x) with f/2.3 to 115mm (5x) with f/3.0 using continuous optical zoom
HPE (1/1.4", 200MP) periscope and new lens group
Engineering prototype with a minimum aperture of F3.0± and a maximum aperture of F2.3± within the variable focal length range
Let's analyze based on the available information
The Xiaomi 15 Ultra uses a 1/1.4" HP9 sensor at 100 mm (4.3×) with f/2.6. Since the Xiaomi 17 Ultra will use the same-sized 1/1.4" HPE sensor, we can use the 15 Ultra’s f/2.6 at 100mm as a reference—aperture scales proportionally with focal length
The ratio between f/3.0 and f/2.6 is 3 ÷ 2.6 ≈ 1.15
New focal length: 100 mm × 1.15 = 115 mm
Xiaomi 15 Ultra: f/2.6 @ 100 mm
Xiaomi 17 Ultra (long end): f/3.0 at 115 mm
The ratio between f/3.0 and f/2.3 is 3 ÷ 2.3 ≈ 1.30
Short end focal length: 115 mm ÷ 1.30 ≈ 88 mm (DCS gave approximate f-numbers, so round to 85 mm)
Thus, the Xiaomi 17 Ultra periscope should span roughly 85mm (3.7x) with f/2.3 to 115mm (5x) with f/3.0 using continuous optical zoom
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POCO F7 : Install OrangeFox Recovery and AOSP ROM - Full installation Guide
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Fox Recovery
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Samsung Electronics confirms February launch of ‘Galaxy S26’ next year… Only the Ultra model to be equipped with a Qualcomm AP
A recent news popped up regarding the Periscope where the aperture is variable in periscope from F2.3 to F3.0 upon zooming,
But the twist is that as per source it could be 85mm-115mm
Xiaomi 17 ultra
But the twist is that as per source it could be 85mm-115mm
Xiaomi 17 ultra
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POCO F7 The SuperiorOS Update Review, Best Performance Results, 120fps and more..
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❤2
Ola 4680 Bharat Cell
• Format: Cylindrical lithium-ion cell
Size: 46 mm diameter, 80 mm height
• Why it matters: Made in India to reduce battery imports and gain control over cost, quality, and supply chain.
• Claims:
* Higher energy density (~275 Wh/kg)
* Faster charging (around 50% in about 13 minutes under ideal conditions)
* Longer usable lifespan and better performance stability
• Production:
Located at the Krishnagiri Gigafactory.
Starting with about 1 GWh capacity.
Planned scale up over time.
• Vehicle Use:
New Ola scooters and motorcycles are expected to adopt this cell gradually from 2025 onward.
• Format: Cylindrical lithium-ion cell
Size: 46 mm diameter, 80 mm height
• Why it matters: Made in India to reduce battery imports and gain control over cost, quality, and supply chain.
• Claims:
* Higher energy density (~275 Wh/kg)
* Faster charging (around 50% in about 13 minutes under ideal conditions)
* Longer usable lifespan and better performance stability
• Production:
Located at the Krishnagiri Gigafactory.
Starting with about 1 GWh capacity.
Planned scale up over time.
• Vehicle Use:
New Ola scooters and motorcycles are expected to adopt this cell gradually from 2025 onward.
⚠️ We Are Losing the AI Race
As I track India’s tech landscape, one truth stands out starkly: India is losing the AI race, and the gap with global leaders is widening at an alarming pace.
---
📊 The Numbers Tell the Story
- 2024: US AI startups raised $199 billion, China raised $9.3 billion, while India managed only $780 million — less than 1% of the US.
- 2025 (Jan–Oct): India raised just $616 million, continuing the downward trend.
This isn’t just a funding gap; it’s a signal of systemic weakness.
---
🚨 Two Foundational Failures
1. A Failure of National Priority
- India spends 0.6% of GDP on R&D.
- Compare this with China’s 2.68% and the US’s 3.5%.
- The message is clear: fundamental innovation is not our national priority.
2. A Crippled Data Infrastructure
- AI thrives on massive, high-quality datasets.
- In India, data is either poorly maintained or owned by foreign tech giants.
- 90% of our digital data is exported, processed abroad, and sold back to us.
- Without sovereign access to data, Indian companies cannot build competitive AI.
---
🧠 The Inevitable Consequence: Brain Drain
- Lack of capital + lack of infrastructure = our best talent leaves.
- Top engineers are moving to Silicon Valley or Singapore.
- Example: Two 25-year-old IIT Kharagpur graduates raised $61 million in the US for their AI startup.
- We educate them, but the value creation happens elsewhere.
---
💡 What Must Be Done
- The government must provide “patient capital” in the form of grants.
- Corporations must invest in foundational AI infrastructure.
- Without this, India will remain a consumer of foreign AI, not a creator of its own.
---
🔮 The Grim Outlook
Unless urgent action is taken, India’s role in the AI revolution will be limited to importing innovation, not leading it.
As I track India’s tech landscape, one truth stands out starkly: India is losing the AI race, and the gap with global leaders is widening at an alarming pace.
---
📊 The Numbers Tell the Story
- 2024: US AI startups raised $199 billion, China raised $9.3 billion, while India managed only $780 million — less than 1% of the US.
- 2025 (Jan–Oct): India raised just $616 million, continuing the downward trend.
This isn’t just a funding gap; it’s a signal of systemic weakness.
---
🚨 Two Foundational Failures
1. A Failure of National Priority
- India spends 0.6% of GDP on R&D.
- Compare this with China’s 2.68% and the US’s 3.5%.
- The message is clear: fundamental innovation is not our national priority.
2. A Crippled Data Infrastructure
- AI thrives on massive, high-quality datasets.
- In India, data is either poorly maintained or owned by foreign tech giants.
- 90% of our digital data is exported, processed abroad, and sold back to us.
- Without sovereign access to data, Indian companies cannot build competitive AI.
---
🧠 The Inevitable Consequence: Brain Drain
- Lack of capital + lack of infrastructure = our best talent leaves.
- Top engineers are moving to Silicon Valley or Singapore.
- Example: Two 25-year-old IIT Kharagpur graduates raised $61 million in the US for their AI startup.
- We educate them, but the value creation happens elsewhere.
---
💡 What Must Be Done
- The government must provide “patient capital” in the form of grants.
- Corporations must invest in foundational AI infrastructure.
- Without this, India will remain a consumer of foreign AI, not a creator of its own.
---
🔮 The Grim Outlook
Unless urgent action is taken, India’s role in the AI revolution will be limited to importing innovation, not leading it.
👏1
📸 Apple’s Next-Gen Mobile Image Sensor with LOFIC
🔑 Key Feature: LOFIC (Lateral Overflow Integration Capacitor)
- Purpose: Expands dynamic range at the pixel level.
- How it works:
- Normal pixels saturate under strong light → highlights blow out.
- LOFIC adds a side capacitor to store overflow charge.
- Enables capturing bright + dark details in one shot, reducing reliance on multi-frame HDR.
---
🍏 Why Apple Wants This
- 🌞 Better highlight preservation while maintaining low-light sensitivity.
- 🎞️ Less multi-frame stacking → fewer motion blur/ghosting artifacts.
- 🧠 On-sensor processing → reduces noise before software correction.
- 🏗️ Vertical integration strategy → aligns with Apple’s A/M chip approach.
---
⚙️ Technical Notes (Patents & Reports)
- Stacked sensor design:
- Light-sensing layer on top
- Logic + memory layer below
- Pixel circuitry includes:
- Photodiode, transfer gate, floating diffusion node, readout transistor, LOFIC capacitor control
- Dynamic range target: ~120 dB (~20 stops) → far above typical smartphone sensors
- Noise calibration: Logic layer circuitry subtracts fixed-pattern noise
---
⏳ Expected Timing
- Possible debut: 2027 high-end iPhone
- Caveat: Based on patents/reports → not guaranteed
---
🚀 Potential Impact
- 🌅 Improved harsh lighting performance (e.g., backlit scenes)
- 🎥 Cleaner HDR video with fewer artifacts
- 📊 Competitive disruption in smartphone imaging
🔑 Key Feature: LOFIC (Lateral Overflow Integration Capacitor)
- Purpose: Expands dynamic range at the pixel level.
- How it works:
- Normal pixels saturate under strong light → highlights blow out.
- LOFIC adds a side capacitor to store overflow charge.
- Enables capturing bright + dark details in one shot, reducing reliance on multi-frame HDR.
---
🍏 Why Apple Wants This
- 🌞 Better highlight preservation while maintaining low-light sensitivity.
- 🎞️ Less multi-frame stacking → fewer motion blur/ghosting artifacts.
- 🧠 On-sensor processing → reduces noise before software correction.
- 🏗️ Vertical integration strategy → aligns with Apple’s A/M chip approach.
---
⚙️ Technical Notes (Patents & Reports)
- Stacked sensor design:
- Light-sensing layer on top
- Logic + memory layer below
- Pixel circuitry includes:
- Photodiode, transfer gate, floating diffusion node, readout transistor, LOFIC capacitor control
- Dynamic range target: ~120 dB (~20 stops) → far above typical smartphone sensors
- Noise calibration: Logic layer circuitry subtracts fixed-pattern noise
---
⏳ Expected Timing
- Possible debut: 2027 high-end iPhone
- Caveat: Based on patents/reports → not guaranteed
---
🚀 Potential Impact
- 🌅 Improved harsh lighting performance (e.g., backlit scenes)
- 🎥 Cleaner HDR video with fewer artifacts
- 📊 Competitive disruption in smartphone imaging
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