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San Francisco Bay Area
Joined November 2013
Arindam Banerji, PhD retweeted
强烈推荐斯坦福的这套关于 AI Agent 的课程,对于有志成为 agent engineer 的同学可以看看:cs329z.stanford.edu/
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Arindam Banerji, PhD retweeted
In 2018, I visited Rohingya bastis in Jammu An intelligence (IB) officer told me he had recorded 1,548 Rohingya families living in the region by then I asked one Rohingya, 60-year-old Sayed Hussain, how he ended up in faraway Jammu after crossing the border in West Bengal. “I boarded the first train I saw [at Kolkata station]. It was noon. The journey ended at Jammu," he said Hussain said he was among the first Rohingya to have settled in Jammu’s Bhatindi area 10 years earlier Another Rohingya, 27-year-old Mohammed Tahir, also gave the same reason Later, the IB officer laughed at this explanation. Told me, “By all accounts, they boarded the Sealdah Express that crosses Bihar, Uttar Pradesh, and Punjab before reaching Jammu. It’s an arduous two-day journey. Why did they not get down at any of the stations in between?” There is a syndicate active in Kolkata that has facilitated Rohingya migration to Jammu for years. They tell the Rohingya that the only Muslim-majority state in India is their "natural home" Ironically, most settle in Hindu-majority Jammu and not Muslim-majority Kashmir. The officer showed me figures on how Rohingya are scattered over 42 sites across Jammu, meaning they are being settled all over the region, and many Army camps were now surrounded by them In 2015, Abdur Rehman al Arkani, a Jihadi killed by security forces in south Kashmir, was from Rakhine from Myanmar. He went by pseudonym “Chota Burmi” Role of several Rohingya men in helping Pakistani Jihadis trespass Jammu border had surfaced by then. They are considered experts in infiltration as they are deft in cutting the fence, know tunneling, and are skilled in camouflage. Plus, they have a victimhood narrative of being wronged by qafirs - the Buddhists of Myanmar In Jammu's Bhatinda are I visited, it was a surprise how quickly they had flourished, as if being pampered and nurtured. An entire lane of shops was called "Burmi market". Most dry fruits factories were employing Rohingya women for cracking walnuts Local Hindus told me how these infiltrators had bigger and better stocked shops than them, who had lived here for generations The officer told me how using the UNHCR cards, which have no legal status or validity in India, Rohingya have obtained Aadhaar cards, ration cards and, in some cases, even permanent resident certificate (PRC) cards, all through fraudulent means Eight years later, these Rohingya are all still there in Jammu. Apparently the govt is running an anti-encroachment drive these days asking them to clear the areas they have illegally occupied, and some of them have reportedly begun to leave But the exercise is looking more like a temporary inconvenience for the infiltrators than a serious effort to clear Jammu and India of them.
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Arindam Banerji, PhD retweeted
Our HT Story: A sample of major Indian-American donors gave Republicans 4:1 funding edge over Democrats ahead of US midterms despite rising anti-Indian views Indian-Am donors gave $15.8 million to Republican groups since 2025 compared to ~$3 mn to Dems hindustantimes.com/india-new…
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Arindam Banerji, PhD retweeted
I'm posting a series of prediction questions from Stanford CS312 (Deep Learning Alchemy) exams to test deep learning intuition. First up: optimization. If we increase an LM's batch size 8× (same token budget), can rescaling learning rate or weight decay compensate? Try below ↓ This quiz is part of our optimizer hyperparameter assignment and unit designed by @wen_kaiyue Setup: We train an 8-layer, ~35M-parameter Transformer on 614.4M tokens using AdamW. At batch size 64, the best reference run has peak LR 0.003, weight decay (WD) 0.2, and final validation loss 2.9178. Now increase the batch size from 64 to 512, which gives 8× fewer optimizer steps. Everything else stays fixed except the changes below. Which recipe gives the lowest final validation loss? A. Keep LR and WD unchanged B. LR ×√8 C. LR ×8 D. WD ×8 E. LR ×√8 and WD ×√8 What would you predict, and why?
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Arindam Banerji, PhD retweeted
Samayun Sheikh, the main guy who killed and cut up BJP worker Sujit Mondal, has been killed in an encounter. If 1,500-2,000 criminals are dealt without mercy in the next 12 months, lawless West Bengal will become like Yogi’s UP in law and order.
#BigBreaking: Second encounter in #WestBengal. On August 28, BJP worker from Murshidabad’s Samserganj, Sujit Mondal went missing & after two days, few of his body parts were recovered. CID took over the case & made three arrests including main accused Samayun Sheikh. Today when CID was conducting crime-scene reconstruction with the accused persons when the main accused Samayun Sheikh snatched the police firearm & tried to flee. He was shot at in police’s retaliatory fire. He was rushed to hospital where he was declared dead.
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Arindam Banerji, PhD retweeted
I read the error analysis chapter of Evals for AI Engineers by @HamelHusain and @sh_reya and realised I already had the dataset. Some backstory. I work with coding agents all day: Claude Code, Codex, Hermes, Antigravity. Every session is a trace. What I typed, every tool call, what came back, what it said. Hundreds of them, sitting on disk, never read. The chapter says: don't start with metrics. Read traces end to end. Mark the first step where it went wrong and write one short note in your own words. Yes or no verdict per trace, no scores out of 5. Only after 20 marked traces do you group them into failure types. And don't let a model invent the categories, it will hand you "hallucination" and miss the ones specific to your system. So I built it into the dashboard I use to watch my agents. Last 14 days, up to 200 sessions per app, 431 when I took the screenshot. Each step has one button: mark this as the failure. Every mark lands in a Failures list with the note and a CSV download. The first failure it found was in the list itself. 193 of the 200 newest Claude rows were "Untitled". My own usage check had been running every 10 minutes and left 1,893 throwaway sessions that pushed the real ones out. Filtered, 117 real sessions named. If the sample is wrong, the reading is wrong before it starts. First real mark: an agent said a metronome app was done before it had looked at it. A stop hook had to force the screenshot. No category yet. Just the note. The agent's answer is not the data. The trace is the data.
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Your report was clearly intended to initiate a witch hunt against CEC Gyanesh Kumar. You cannot make such serious allegations and then just hand wave your way out of it. The EC’s unanimous affidavit is very strong evidence against the claim that the three SIR orders were imposed without approval. Internal objections are simply evidence that a disagreement occurred, NOT that the institution acted unlawfully. If internal disagreements are being used to cast doubt on the integrity of an institution, then the same evidentiary standard should apply to ALL former ECs under the Congress regime too and all their records need to be investigated.
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Arindam Banerji, PhD retweeted
last week we closed the Training Agents series IRL at the GitHub offices in SF 4 talks, a panel and audience Q&A. almost 2h on post-training agents with open models > Learnings from enterprise RL (@t2govind Microsoft) > Environments and benchmarks in industry (@VBarres86633 Mercor) > How to train your agents with Miles (@nblintao RadixArk) > Why we built OpenEnv Arena (@xdotli BenchFlow) full recording + slides youtube.com/watch?v=CKFUx7CO…
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Arindam Banerji, PhD retweeted
▲ Meet LEANN: An Open-Source Vector Index that Shrinks a 60M-Chunk RAG Index from 201 GB to 6 GB The key idea is simple: graph search only touches a few nodes per query. So LEANN stores a pruned graph plus small PQ codes. It re-embeds only the nodes on the search path, in GPU batches. On a 76 GB Wikipedia corpus, LEANN needs 4 GB. HNSW needs 188 GB. Both hit 25.5% NQ accuracy at 90% recall. It is a trade-off though: retrieval takes 2.48 s vs 0.05 s for HNSW, and 44.80 s on HotpotQA on an M1 Ultra Mac. MIT licensed, pip install leann, and it won Best Research Paper at MLSys 2026. Numbers are self-reported...... Full analysis: marktechpost.com/2026/10/27/… Repo: github.com/StarTrail-org/LEA… Paper: arxiv.org/abs/2506.08276 PyPI: pypi.org/project/leann
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Arindam Banerji, PhD retweeted
He was 25, flying home from his honeymoon with his 20 year old wife. Terrorists hijacked the plane and killed him within hours. For eight days his wife sat on the same plane and did not know. His name was Rupin Katyal, from Delhi. In December 1999 he married Rachna. They went to Nepal for their honeymoon. On 24 December 1999 they boarded IC 814 from Kathmandu to Delhi. Soon after takeoff, five terrorists hijacked it. Within hours they stabbed Rupin to death. The plane went to Amritsar, Lahore, Dubai and finally Kandahar. For eight days the passengers sat as hostages. Rachna did not know her husband was dead. On 31 December 1999 India released three terrorists to free the hostages. One of them was Masood Azhar. Weeks later he founded Jaish e Mohammed. Nobody has ever been punished for killing Rupin.
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Arindam Banerji, PhD retweeted
Given some semi-literate Indian commentators are celebrating the putative exit of Netanyahu, I’m just posting this summary of his putative replacement: Gadi Eisenkot and the Dahieh Doctrine he developed. Enjoy 😂 Le roi est mort, vive le roi!
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Arindam Banerji, PhD retweeted
Replying to @BriciusX
Yes. Albert Speer's memoir records Hitler privately saying the Mohammedan religion would have been far more compatible with the Germanic temperament than Christianity's "meekness and flabbiness." Similar private remarks appear in Table Talk accounts praising Islam's warrior ethos, though those transcripts face authenticity questions from some historians.
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Arindam Banerji, PhD retweeted
Great paper from Alibaba and Cornell on verification in coding-agent harnesses. (bookmark it) If you build agent harnesses, this one is worth your time. They find that a separate reviewer agent adds 5.9 to 9.5 points on Terminal-Bench at 1.13 to 1.25x the baseline cost. They compared 17 verification designs across seven frontier coding models on Terminal-Bench and SWE-bench Verified. The designs check the agent's work at four points: the initial instructions, reminders during the run, a gate before the agent can finish, and an independent critic at the end. Instructions and reminders gave small, model-dependent gains. Completion gates gave larger gains, sometimes at much higher cost. The critic gave the best accuracy per dollar, adding 3.9 to 6.6 points on SWE-bench Verified at almost no extra cost. More review rounds added up to 3.5 more points on Terminal-Bench. arxiv.org/abs/2610.34577 Chat with Paper: academy.dair.ai/papers/rethi…
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Arindam Banerji, PhD retweeted
Must-read paper from Microsoft Research and Georgia Tech. This one has lots of great insights. They used 163,487 Reddit posts about AI agents and surveyed 73 experienced agent users to map how delegated agent work goes wrong. The result is MANDATE, a taxonomy of 23 failure categories in seven groups. Each describes an agent that finishes the job in a way the user didn't expect. Users rated the most severe failures as the hardest to notice. People who had already run into a failure found it easier to spot than people who only thought it was possible. The most common failures are often the least studied. Agents that keep running and spend time and compute without making progress are among the most commonly reported failures, and they have the thinnest research base. arxiv.org/abs/2610.34748 Chat with Paper: academy.dair.ai/papers/babys…
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Arindam Banerji, PhD retweeted
He is Jayabalakrishnan, a street food vendor in Kochi, Keralam. He was killed when a Mercedes-Benz driven by the 17-year-old minor son of an Additional District Judge rammed into his scooter. Result: The accused son of a Judge got bail in 3 hours.
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Arindam Banerji, PhD retweeted
She lied about literally everything. Literally every single thing. Trashy unethical editors & a repeat pattern of promoting trashy reporters
‘SIR decisions unanimous’: EC to Supreme Court; but big question unanswered Reported by: @RitikaChopra__ Read: indianexpress.com/article/in…
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Arindam Banerji, PhD retweeted
Name & shame in the Kerala Judge’s teenager Mercedes death case: Judge father: Reno Xavier Juvenile Board Officer who granted quick bail: Rohit Nandakumar Policemen: CI Shyam, SHO Vishwajith, CPO Arun & ASI Manoj
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Arindam Banerji, PhD retweeted
The detailed affidavit filed by @ECISVEEP has taken the wind out of the sails of Congress and its army of unemployed anarchists, disgruntled Supreme court judges, dynasty doormat CECs, and sold out journalists hoping for a quick regime change. Rahul, it's done bro. My views:
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Arindam Banerji, PhD retweeted
To prove Kerala's secularism I am opening a restuarant called Makkah which is a Hebrew word meaning Plague. I will be serving only Pork dishes and will install artwork of Netanyahu and Jinnah. Ideally outside a mosque...
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Arindam Banerji, PhD retweeted
₹50 हजार सैलरी 'नेचर' को 'नथूरे' पढ़ा रहे मध्य प्रदेश के अनोखे शिक्षक: 'एजुकेशन' की स्पेलिंग 'AGUQUSAN' लिखी, उपराष्ट्रपति का नाम भी नहीं पता; TET के विरोध के बीच दैनिक भास्कर की पड़ताल में चौंकाने वाले सच पूरा वीडियो देखने के लिए लिंक पर क्लिक करें-dainik.bhaskar.com/fdHk6GsZx… #MPNews #HindiNews #Investigation #BhaskarInvestigation #MP #Teachers #MPSchoolNews #TET #Chhatarpur #Rajgarh
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