Why Kosi Channel needed: Heavy silt deposition in Kosi raises riverbed, diverts flow towards embankments, increasing flood and breach risk in north Bihar.
Benefit: The pilot channel diverts excess flow, reduces pressure on embankments, and maintains smoother river flow, thereby minimising flood risk during monsoon.
—>Proposed high dam on Kosi in Nepal aims for permanent flood control, but remains stalled due to India–Nepal disagreements on cost, benefits, and rehabilitation issues.
—>Seismic risks, environmental concerns, and political delays have further slowed progress.
—>As a result, Bihar continues to rely on temporary flood-management measures instead of a long-term solution.
#GS2mains
Benefit: The pilot channel diverts excess flow, reduces pressure on embankments, and maintains smoother river flow, thereby minimising flood risk during monsoon.
—>Proposed high dam on Kosi in Nepal aims for permanent flood control, but remains stalled due to India–Nepal disagreements on cost, benefits, and rehabilitation issues.
—>Seismic risks, environmental concerns, and political delays have further slowed progress.
—>As a result, Bihar continues to rely on temporary flood-management measures instead of a long-term solution.
#GS2mains
1. Three Ganga Path Projects (Bihar):
• Ganga Amrit Path —> Bidupur to Dighwara (≈56 km)
• Narayani Path —> Darihara (Saran) to Dumariya Ghat (Gopalganj) (≈73.51 km)
• Vishwamitra Path —> Buxar – Ara – Maner (≈90 km)
• All part of North Ganga Path; to be executed on PPP model (DBFOT) by BSRDCL
2. Education Sector Scheme:
• Unnat Shiksha – Ujjwal Bhavishya Scheme
• Aim: One model school (Adarsh Vidyalaya) in each block
3. 2025–30 Target (Education):
• Under 7-Nischay (2025–30) framework
• Upgradation of government schools into “centres of excellence”
Key components:
• Modern science & computer laboratories
• Smart classrooms
• Standardised academic + co-curricular curriculum
• Defined criteria for teacher & student selection
• Aim: Bring govt schools at par with national standards
#BIHARspecial
#GS2mains
• Ganga Amrit Path —> Bidupur to Dighwara (≈56 km)
• Narayani Path —> Darihara (Saran) to Dumariya Ghat (Gopalganj) (≈73.51 km)
• Vishwamitra Path —> Buxar – Ara – Maner (≈90 km)
• All part of North Ganga Path; to be executed on PPP model (DBFOT) by BSRDCL
2. Education Sector Scheme:
• Unnat Shiksha – Ujjwal Bhavishya Scheme
• Aim: One model school (Adarsh Vidyalaya) in each block
3. 2025–30 Target (Education):
• Under 7-Nischay (2025–30) framework
• Upgradation of government schools into “centres of excellence”
Key components:
• Modern science & computer laboratories
• Smart classrooms
• Standardised academic + co-curricular curriculum
• Defined criteria for teacher & student selection
• Aim: Bring govt schools at par with national standards
#BIHARspecial
#GS2mains
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Fundamentals_of_Physical_Geography_annotated_&_Value_added.pdf
122.1 MB
Fundamentals_of_Physical_Geography_annotated_&_Value_added.pdf
India Physical Environment value added & annotated .pdf
24.8 MB
India_Physical_Geography_annotated_&_Value_added.pdf
AGRICULTURE INDIA & BIHAR_BPSCWEB.pdf
40.3 MB
AGRICULTURE INDIA AND BIHAR
BPSC 69 & 70 source tracing_NCERTs.pdf
18.6 MB
BPSC 69 & 70 source tracing_NCERTs.pdf
FLFPR
Labour Force Participation Rate (LFPR) in usual status (ps+ss) for persons of age 15 years and above observed as 59.3% during 2025 and remained stable compared to 2024. The same for male and female stood at 79.1% and 40.0%, respectively, in 2025.
Link: https://t.me/bpscweb/43382
#CA2026
#DATA
👇🏻👇🏻
Labour Force Participation Rate (LFPR) in usual status (ps+ss) for persons of age 15 years and above observed as 59.3% during 2025 and remained stable compared to 2024. The same for male and female stood at 79.1% and 40.0%, respectively, in 2025.
Link: https://t.me/bpscweb/43382
#CA2026
#DATA
👇🏻👇🏻
AI Companies —> Models (with function)
• OpenAI —> GPT (text/LLM), DALL·E (image), Whisper (speech-to-text), Codex (coding)
• Google DeepMind —> Gemini (multimodal), Imagen (image), Veo (video), AlphaFold (protein)
• Anthropic —> Claude (LLM, safety-focused)
• Meta —> LLaMA (open LLM)
• xAI —> Grok (real-time conversational AI)
• Mistral AI —> Mistral (efficient LLM), Mixtral (MoE LLM)
• DeepSeek —> V-series (LLM, reasoning/coding)
• Microsoft —> MAI (multimodal—voice/image)
• Stability AI —> Stable Diffusion (image)
• Midjourney —> Midjourney (image)
#CA2026
• OpenAI —> GPT (text/LLM), DALL·E (image), Whisper (speech-to-text), Codex (coding)
• Google DeepMind —> Gemini (multimodal), Imagen (image), Veo (video), AlphaFold (protein)
• Anthropic —> Claude (LLM, safety-focused)
• Meta —> LLaMA (open LLM)
• xAI —> Grok (real-time conversational AI)
• Mistral AI —> Mistral (efficient LLM), Mixtral (MoE LLM)
• DeepSeek —> V-series (LLM, reasoning/coding)
• Microsoft —> MAI (multimodal—voice/image)
• Stability AI —> Stable Diffusion (image)
• Midjourney —> Midjourney (image)
#CA2026
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Consider the pairs:
1. Whisper — Speech recognition
2. DALL·E — Image generation 3. AlphaFold — Protein structure prediction 4. Veo — Video generation Which of the pairs given above are correct?
1. Whisper — Speech recognition
2. DALL·E — Image generation 3. AlphaFold — Protein structure prediction 4. Veo — Video generation Which of the pairs given above are correct?
Anonymous Quiz
2%
A. 1 and 2 only
34%
B. 1, 2 and 3 only
10%
C. 2, 3 and 4 only
54%
D. 1, 2, 3 and 4
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