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In two intelligence-led ops, Punjab Police India has busted Babbar Khalsa International terror modules backed by ISI from #France, #Greece & #Pakistan. Total 13 operatives arrested from both modules Recovery: 2 RPGs (incl. launcher),2 IEDs (2.5 kg each), 2 kg RDX (remote-controlled), 2 grenades with detonators, 5 pistols (Beretta...

31,109 просмотров • 1 год назад •via X (Twitter)

Комментарии: 8

Фото профиля Doabe Ala
Doabe Ala1 год назад

@PunjabPoliceInd I have trust issues with Punjab police! Can’t trust what they say! Especially the game planted against Amritpal Singh.

Фото профиля ਗੱਜਣ ਸਿੰਘ گجن سنگ
ਗੱਜਣ ਸਿੰਘ گجن سنگ1 год назад

@PunjabPoliceInd Fake propaganda machine India 🇮🇳 terrorist empire

Фото профиля Sikh Policy Center(www.sikhpc.org)
Sikh Policy Center(www.sikhpc.org)1 год назад

@PunjabPoliceInd what a clown. So the paki inteligence sitting in frace, greece and paki is funding 13 people and all this funding could afford was abunch of low grade weapons? I call this bull.

Фото профиля Jag DB
Jag DB1 год назад

@PunjabPoliceInd

Фото профиля HaRRY
HaRRY1 год назад

@PunjabPoliceInd Tusi mama aap terrorist o 😂chita tah ruk ni reha tuhade kolo fake encounter kri jayo 😂

Фото профиля Neverforget1984
Neverforget19841 год назад

@PunjabPoliceInd 😂😂😂🤣all fake arrests.

Фото профиля Aditya kr Das
Aditya kr Das1 год назад

@PunjabPoliceInd Good job @DGPPunjabPolice sir

Фото профиля Bharat
Bharat1 год назад

@PunjabPoliceInd I am proud of KHAKHI as said by DGP but i am safe with OLIVES...@manaman_chhina @TinyDhillon @Vedmalik1 ...anyone who differs we as Indians feel absolutely safe with Olives...can we say the same about Khakhi...

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12,194 просмотров • 2 лет назад

PAKISTAN AND GLOBAL TERRORISM ⚠️ Let’s not forget terrorism isn’t just a problem there—it’s practically a national export. Without it, what would be left of the brand Pakistan? Ending terrorism would be like Coca-Cola discontinuing soda. Some things are just essential for business. Some famous Pakistani brands Al- Qaeda , Jaish E Mohammad(JEM) , Lashkar-e-Taiba(LeT), Osama Bin Laden, ISIS, Haqqani Network, Tehrik-i-taliban(TTP). Many of these groups have operated openly in Pakistan under new names or as “charities” despite being banned. Several have also had alleged ties with elements of Pakistan’s intelligence services, which has fueled global suspicion and FATF sanctions. PAKISTAN & TERROR ATTACKS. 1). 1993 - USA World Trade Center Bombing , Ramzi Yousef, the mastermind, trained in terror camps in Pakistan. He traveled with a Pakistani passport and had links to extremist networks operating freely within Pakistan. #WTC1993 2). 1999 - Kargil War & Militants Pakistan’s military used militants from groups like Lashkar-e-Taiba and Jaish-e-Mohammed as part of its Kargil infiltration into Indian territory—blurring the line between army and jihadist. #KargilWar 3). 2001 - Indian Parliament Attack Five armed terrorists from Pakistan-based Jaish-e-Mohammed attacked the Indian Parliament. India blamed Pakistan and nearly went to war. #DelhiAttack 4) 2001 - 1/ On September 11, 2001, the world changed forever. 19 terrorists hijacked 4 planes in the U.S., killing 2,977 people in coordinated attacks on the World Trade Center, Pentagon, and in Shanksville, Pennsylvania. Attackers were trained in Pakistan by Al Quaeda and ISI links. Pakistan use terrorist as strategic asset . Later Osama was arrested by US seals from safe house just 1Km from Pakistan military academy. #September11 #911Attacks 5). 2008 - Mumbai Attacks (26/11) 10 LeT terrorists attacked Mumbai. They were trained and guided from Pakistan. Voice intercepts exposed Pakistani handlers. The only captured attacker, Ajmal Kasab, was a Pakistani national. 160 people were killed. #MumbaiAttacks 6). 2011 – Osama bin Laden in Abbottabad The world’s most wanted terrorist, Osama bin Laden, was found living in a compound near Pakistan’s military academy. The U.S. carried out a secret raid without informing Pakistani authorities. #BinLaden #Abbottabad 7). 2019 Pulwama Attack A suicide bombing by Jaish-e-Mohammed killed 40 Indian paramilitary personnel. The bomber was Indian, but the group that claimed responsibility is based in Pakistan. #Pulwama Pakistani citizens were caught abroad (e.g., in US. Europe, Gulf) involved in Lashkar-E-Toiba , Jaish , ISIS-linked activities, including financing, recruitment, and attempted attacks in foreign soils. Pakistan PM called Osama Bin Laden as a martyr who has carried biggest terrorist attack in history of US. Still west thinks india should negotiate with Pakistan for de-escalation. Pakistan—the proud global hub where roughly 90% of UN-banned terrorist organizations just happen to emerge. Coincidence, surely. And the fact that nearly every major terror attack in the West has some trail leading back there? Just an unfortunate streak of bad luck. A nation so “democratic” that its military has been the real CEO since 1947, while its prime ministers either end up exiled, imprisoned, or conveniently both. One’s sipping tea in London, the other Imran Khan is behind bars—classic governance! Just see how two previous foreign ministers of Pakistan glorifying Osama Bin Laden and terror activities carried out by their nation. 👇 Truly Pakistan is “MECCA OF TERRORISM”

Maj Digvijay Singh Rawat, Kirti Chakra (Retd)

44,395 просмотров • 1 год назад

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Jacob in Cambodia 🇺🇸 🇰🇭

60,719 просмотров • 3 месяцев назад

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Aladeen

19,981 просмотров • 1 год назад

Milestone! We (robotic arms for gadgets assembly) finished the first commercial order, which brought the first revenue. Here are some learnings from this: The customer was a smart toy manufacturer. The task was to add a heatsink to Raspberry Pi. We received parts from them and returned the assembled modules back. Currently, it's done by teleoperation. Later it will be done by a remote employee via the Internet. Then it will be automated action by action, reducing the operator's time on this and making the task profitable. ps. If you have an assembly task that we can do for you asynchronically - leave a comment below. Learning 1. It's possible! This task which is usually done by the human arm with 5 fingers can be done with a two-finger gripper with the addition of a couple of simple tooling. The task was not simplified. We peeled off thin films from stickers, unpacked paper boxes, moved PCB boards full of components, etc. And no unsolvable problems have been encountered yet. Challenges: 1) The paper box shifted during the opening Solved with the plastic walls that you can lean against 2) Heat pad, stuck to the gripper instead of heat sync. Can be solved by gripper with a pump, but this time solved with the patience of the operator 3) The film on the pad is very thin. Turned out that sub-millimeter arm precision is enough to peel it off with just a regular gripper. 4) The working area has not enough space. You'll only know this by doing real tasks in bulk. This could be solved by an extra pair of long arms, but in this case, solved with the patience of the operator. I think that in the end, we will have 5-10 types of universal tooling and 5-10 types of grippers to solve almost all the problems in such assembly tasks. Learning 2. It's slow. It took 5 times more time, than doing it with human hands. But the good news is there's a lot of room for improvement. We now have specific “time for task” metrics, which we will decrease with iterations. The main reasons for slowness: 1) To rotate the gripper to a steep angle you are forced to control one robot arm with two hands instead of using both arms. We can fix this by just making more room for rotations. 2) Grabbing PCB board with two arms is hard. A slight difference in rotation can break the board, and it's hard to control these angles visually. To solve this, the best way is to use force feedback so you can feel the pressure applied to the item. 3) Accuracy and steadiness is still can be improved We will try a metal version and double the motors to do this. 4) It is physically difficult for the human hands to move with such precision To solve this, we will add a pad for the hands like in surgical robots Learning 3. It's a good business model The "Factory in the cloud" is a good business model for this stage. You send us parts and we send back assembled modules. Currently, it's more convenient than sending a robot to your place, as we can iterate/fix the robot quickly and utilize it 100% of the time. When we polish the set-up over time - we can send robots to your place. So if we can assemble something for you in the USA with Chinese prices by using modern automation - leave a comment below.

Igor Kulakov

37,266 просмотров • 1 год назад

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Nigeria Police Force

84,451 просмотров • 23 дней назад

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FORCE PUBLIC RELATIONS OFFICER

15,520 просмотров • 29 дней назад

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Mohammad Ali Arafat

42,222 просмотров • 1 год назад

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BhikuMhatre

135,375 просмотров • 4 месяцев назад

"Hindu Hriday Samrat" Spits on Hindus 1. On 22 April 2025, Muslims slaughtered 25 Hindu men after religious profiling in #PahalgamTerroristAttack. 2. Immediately, #PseudoHindutva RSS-BJP and "Hindu Hriday Samrat" accused Pakistan without any evidence, to cover up their utter incompetence, if not any other thing. 3. Their propaganda machinery cleverly diverted the genocidal attack on Hindus by Muslims as an Indo-Pak issue. 4. Then they took India to war but called it off in 3 days prematurely (#ceasefire) without achieving any purpose. It turned out to be an expensive fireworks and laser show, making a fool of gullible Hindus. 5. Immediately thereafter, from 13 May 2025 onwards, the RSS-BJP-Modi launched an election campaign in the name of #TirangaYatra. 6. Now they have roped in Asaduddin Owaisi, MP from Hyderabad of AIMIM party, and a few other opposition MPs to tour different countries and tell them about Islamic terrorism by Pakistan and #OperationSindoor. 7. This is the same AIMIM (All India Majlis-e-Ittehadul Muslimeen), which was called the Razakar Party, under the leadership of Qasim Rizvi, indulged in one of the worst forms of Islamic Jihad and genocided lakhs of Hindus in the late 1940s with impunity. 8. Akbaruddin Owaisi, who is a local MLA of AIMIM party and brother of Asaduddin Owaisi, has been openly threatening to genocide Hindus with impunity. Watch this video clip👇. This is an unimpeachable evidence that AIMIM has not abandoned its ideology of violence and religious genocide of Hindus and continues to subscribe to it de facto. 9. Notably, since at least the 1980s, both BJP and AIMIM have been growing politically in Telangana in cahoots with each other, by creating communal polarisation. 10. Now, the "Hindu Hriday Samrat" and his RSS-BJP spit on Hindus by engaging the MP of the same Razakar Party, which massacred lakhs of Hindus, whose brother openly terrorises to genocide Hindus, to lead delegation to foreign countries to expose Pakistan's support for Islamic terrorism.

M. Nageswara Rao IPS (Retired)

30,220 просмотров • 1 год назад

Training Volume / Intensity / Rep Range / Progressive Overload — Everything You Need To Know: (This is what will grow MOST people best) 𝗧𝗢𝗧𝗔𝗟 𝗦𝗘𝗧𝗦 𝗣𝗘𝗥 𝗪𝗘𝗘𝗞 45ish-60ish total working sets per week - If training 3x per week, this will mean 16, 17, 18ish sets per session - If training 4x per week, this will mean 13, 14, 15ish sets per session - If training 5x per week, this will mean 10, 11, 12ish sets per session 𝗧𝗢𝗧𝗔𝗟 𝗦𝗘𝗧𝗦 𝗣𝗘𝗥 𝗕𝗢𝗗𝗬 𝗣𝗔𝗥𝗧 𝗣𝗘𝗥 𝗪𝗘𝗘𝗞 - For balanced development, you’re going to want to perform 5, 6, 7, 8ish sets per body part per week - If prioritizing a muscle group, you’re going to want to perform 8, 9, 10, MAYBE 10+ sets for that body part each week - If deprioritizing a muscle group, you only need 2, 3, 4ish sets for that body part each week to maintain existing development 𝗙𝗥𝗘𝗤𝗨𝗘𝗡𝗖𝗬 In all likelihood, you will get MORE (in the way of stimulus) by splitting the work you do for a given muscle group across 2 sessions per week Splitting the work you do for a given muscle group across 3 sessions per week can work as well but the potential benefit is probably NOT that large and it diminishes the margin of safety Performing all the work you do for a given muscle group on ONE day (Bro Split Style) can work but it like has an opportunity cost associated with it 𝗧𝗢𝗧𝗔𝗟 𝗦𝗘𝗧𝗦 𝗣𝗘𝗥 𝗘𝗫𝗘𝗥𝗖𝗜𝗦𝗘 The sweet spot is generally 2-3 sets for a given exercise in a given session 1 set is fine depending on the context of the programming as a whole but you likely didn’t squeeze all the juice out of the lemon If you preform 4+ sets of a given exercise in a given session, what the fuck were you doing the first couple of sets? 𝗜𝗡𝗧𝗘𝗡𝗦𝗜𝗧𝗬 The intensity you take sets to can GREATLY IMPACT how many total sets you can perform while still allowing for adequate recovery from session to session Generally speaking, it is a good idea to leave about 1 RIR on most exercises to ensure stimulus is robust but fatigue is kept at bay There is one HUGE caveat to that however: If you do not trust your ability to accurately gauge RIR, it is better to just take your sets to 0 RIR/Failure than it is to risk sandbagging sets by leaving an incidental 2, 3, 4+ reps in the tank…just know you will not be able to generate as high a net stimulus throughout the week if you live in this intensity range 𝗥𝗲𝗽 𝗥𝗮𝗻𝗴𝗲/𝗣𝗿𝗼𝗴𝗿𝗲𝘀𝘀𝗶𝘃𝗲 𝗢𝘃𝗲𝗿𝗹𝗼𝗮𝗱 Pick a weight you can do for 5-6ish reps with GOOD-GREAT technique @ the prescribed RIR (should be 0-2 RIR) Once you can hit 7, 8, 9, 10ish reps with the same GOOD-GREAT technique @ the prescribed RIR, increase the load You can weight select on a SET BY SET BASIS — this means in theory some of your sets could be heavier/lighter than others (assuming you’re doing multiple sets of a given exercise on a given day)

Dean Turner

18,116 просмотров • 6 месяцев назад

RLHF by hand ✍️ ~ 15 steps walkthrough below Train a model on human text and it inherits human bias. It will assume a doctor is a "him", because the data says so. RLHF is the correction. A human marks one preference, doc is them over doc is him, and the weights move. But one correction is not the point. The hope is that the model learns the value behind it, gender neutrality, and applies it to professions nobody ever mentioned. How does it work? Goal: train a reward model from a single human comparison about doctors, then turn it on CEOs, filling in every cell yourself. = 1. Given = A reward model, an LLM, and two (prompt, next) pairs. = 2. Preferences = A human reads both pairs and picks a winner: (doc is, them) beats (doc is, him). The loser is not bad grammar, it is gender bias, and that is the whole signal. = 3. Word embeddings = Let us look up each word of the loser pair. These vectors are the reward model's input. = 4. Linear layer = We multiply by the reward model's weights and add its biases. Out come feature vectors, one per position. = 5. Mean pool = Let us multiply by [1/3, 1/3, 1/3], which averages the three positions into one sentence embedding. = 6. Output layer = We map that sentence down to a single number. Reward = 3. = 7. The winner, the same way = Let us repeat steps 3 to 6 on the winning pair. Reward = 5. = 8. Winner minus loser = We take the gap: 5 - 3 = 2. The reward model wants this positive and as large as it can make it. = 9. Loss gradient = Let us squash the gap into a probability, σ(2) ≈ 0.9, and subtract the target of 1. The gradient is -0.1, and it goes back through the purple weights. The reward model is now trained. = 10. A prompt it has never seen = We start the second half with "[S] CEO is". The feedback in step 2 was about doctors. Nothing connects a CEO to a doctor except what the reward model generalised. = 11. Transformer = Let us push it through attention and a feed forward layer, one vector per position. = 12. Output probabilities = We map each vector to a score over the vocabulary. = 13. Sample = Let us take the highest score. The model completes "CEO is" with "him", which is the same bias the human penalised in step 2. = 14. Score it with the reward model = We feed the new pair (CEO is, him) through steps 3 to 6. Reward = 3, exactly the score it gave "doc is him" in step 6. Nobody taught it about CEOs. The value transferred. = 15. Loss gradient = Let us set the loss to the negative of the reward, so minimising the loss maximises the reward. The gradient is a constant -1, and it goes back through the red weights. The outputs: Loser reward = 3, winner reward = 5 Reward gap = 2, predicted σ ≈ 0.9, reward model gradient = -0.1 LLM samples "him", reward = 3, LLM gradient = -1 Congrats! You just calculated RLHF by hand. And you watched a value generalise: one comparison about doctors, and the model marks down "CEO is him" unprompted. 💾 Save this post!

Tom Yeh

22,105 просмотров • 26 дней назад

BIDEN'S REAL AGENDA IN ANGOLA Biden's gone to Angola for the loot, specifically for minerals like cobalt and copper necessary for powering devices and electric vehicles. That's educator George Lee Jr's blunt assessment of US President Joe Biden's 11th-hour visit to Angola on 2 December. The outgoing president’s tour will include the $5 billion Lobito Corridor, a key infrastructure project co-funded by the United States and the European Union that connects Angola's port of Lobito on the Atlantic coast to the mineral-rich Democratic Republic of the Congo (DRC) and Zambia via a 1,300-kilometre railway. Lee argues the project will only hasten the exploitation of Angola and the DRC. It's part of Washington's effort to counter China's economic clout in Africa. Angola's strategic location on the southwest coast of Africa has long made it a key player in international affairs. It's a convenient export point for goods from Central Africa to the West. However, it's also been central to significant historical events, including a proxy war between Cold War rivals. Moscow backed the Popular Movement for the Liberation of Angola (MPLA) led by Agostinho Neto, while Washington supported the National Front for the Liberation of Angola (FNLA) and its offshoot, the National Union for the Total Independence of Angola (UNITA), led by Jonas Savimbi. The civil war began in 1975 and ended in 2002. Following the war's end, China provided infrastructure development loans that sped up Angola's economic recovery. In turn, China gained access to Angola's oil industry, which now supplies 72 per cent of its output to China. Given China's heavy investments in the region's mining industry, the jury is out on whether Washington can catch up with Beijing. Video credit: Conscious Lee (X)

African Stream

27,973 просмотров • 1 год назад