正在加载视频...

视频加载失败

We ran a major bug bounty programme. Significant prize pool. Zero findings. But that's just one layer. Internal security audits, external audits, pen testing, chain integrity is our number one priority by a long way. If the base layer is compromised, nothing else matters.

13,164 次观看 • 4 个月前 •via X (Twitter)

27 条评论

Leo XBT 的头像
Leo XBT4 个月前

@Somnia_Network Really awesome to see the security measures taken for Somnia I believe the chain will definitely shine harder in the near future

eltanque.somi 的头像
eltanque.somi4 个月前

THIS is Somnia🖤

Sanjeeb Das 的头像
Sanjeeb Das4 个月前

Respect bro, strong security first is how real trust gets built. Somnia matters most

Janaro 的头像
Janaro4 个月前

I think the biggest challenge is yet to come, the taller the tree the stronger the wind that hits it.

Kolcent 的头像
Kolcent4 个月前

respect that approach

Klvn 的头像
Klvn4 个月前

Agree with you Peter 🤝

Sofiya🇺🇦 的头像
Sofiya🇺🇦4 个月前

Somnia should be safe.

Hexor 🗿 的头像
Hexor 🗿4 个月前

How often are you rotating auditors or refreshing your testing approach?

Jack 的头像
Jack4 个月前

audits are great but users need to stay vigilant too

Vito Botta 的头像
Vito Botta4 个月前

Zero findings on a big prize pool is genuinely impressive. Most programmes get flooded with low-hanging fruit.

Tony 的头像
Tony4 个月前

@Somnia_Network Excellent result Peter

Mogi 的头像
Mogi4 个月前

somnia in safe hand

👑 Winston👑 的头像
👑 Winston👑4 个月前

@Somnia_Network You failed to invite Lazarus!

Tim Arno 的头像
Tim Arno4 个月前

Great step for a big adoption 🤝

Trastew 的头像
Trastew4 个月前

based

0xAlex 的头像
0xAlex4 个月前

good to always host bounty programs like this security matters a whole lot

joker101010 的头像
joker1010104 个月前

Now, April is coming to an end, and Somnia has never gone up properly, but it continues to fall. This time, I got it right as I said. Some Somnia advocates said they'd watch for two weeks until the end of April. I guess it's gone now?As expected, the price of Somnia doesn't go up

Ayan 的头像
Ayan4 个月前

Great Approach by Somnia

Dhruv (Revived) 的头像
Dhruv (Revived)4 个月前

Great to know this... The best chain needs to have the best security systems too

0xJames 🛰️ 的头像
0xJames 🛰️4 个月前

Massive captain 🫡

Base.eth 的头像
Base.eth4 个月前

Bảo mật hết sức quan trọng, hãy làm cho SOMI ko thể xâm nhập từ những kẻ xấu

Gold Crypto 的头像
Gold Crypto4 个月前

لا تنخدع بهؤلاء المحتالون انظر الى طريقته في الكذب والاحتيال على الناس فتح شمعه من 17 سنت الى 25 سنت ثم عاد مره اخرى اياك ان تدخل هذه العمله المحتاله فلو ان لديهم مشروع حقيقي لوجدتهم حريصين على ان لا يكون شكل الشارت بهذا العفن عمله احتيال حتى لو شاهدت انك تربح سينزل بالسعر

joker101010 的头像
joker1010104 个月前

Somnia is also falling in price. Somnia has never been maintained because the price has gone up properly. The price goes down right away. Don't believe Somnia if it doesn't rise or hold above $0.5. It's definitely going down.

Margie Naomi 的头像
Margie Naomi4 个月前

We take our security incredibly seriously, constantly testing and updating to ensure the protection of our systems

Lincos 🚢 Web3 Contributor 的头像
Lincos 🚢 Web3 Contributor4 个月前

@Somnia_Network I like what you are working on.

Shufcop 的头像
Shufcop4 个月前

Excellent result Keep it up💪

Shawn 的头像
Shawn4 个月前

Believe in Somnia

相关视频

Backpropagation by hand ✍️ ~ 11 steps walkthrough below Backpropagation is the algorithm that actually trains a neural network, and it is where most people stop following along. It is not calculus you cannot do. It is matrix multiplication, working backward, one layer at a time. So I drew and calculated one entirely by hand. Goal: push the loss gradient back through a 3-layer network and land on a new value for every weight and bias. = 1. Given = A 3-layer perceptron, an input X, predictions Ypred = [0.5, 0.5, 0], and the truth Ytarget = [0, 1, 0]. = 2. Backprop gradient cells = Let us draw empty cells for every gradient we are about to compute. The shape of the answer comes first. = 3. Layer 3 softmax = We get dL/dz3 straight from Ypred minus Ytarget = [0.5, -0.5, 0]. No chain rule needed, and that shortcut is the whole reason softmax and cross-entropy are paired. = 4. Layer 3 weights and biases = Let us multiply dL/dz3 by [a2 | 1]. One multiplication gives the gradient for W3 and b3 together. = 5. Layer 2 activations = We multiply dL/dz3 by W3 to get dL/da2. The gradient moves back across a layer the same way the signal moved forward. = 6. Layer 2 ReLU = Let us pass it through the gate: keep the gradient where the activation was positive, zero it everywhere else. = 7. Layer 2 weights and biases = We multiply dL/dz2 by [a1 | 1]. The same figure as step 4, one layer up. = 8. Layer 1 activations = Let us multiply dL/dz2 by W2. = 9. Layer 1 ReLU = We apply the same gate again, now on a1. = 10. Layer 1 weights and biases = Let us multiply dL/dz1 by [x | 1], and every weight in the network now has a gradient. = 11. Update = We subtract, and the network has learned. In practice a learning rate scales this step. The gradients: dL/dz3 = [0.5, -0.5, 0] dL/da1 = [1, -2, 2, -1] dL/dz1 = [0, -2, 2, -1] The takeaway: matrix multiplication is all you need. Just like the forward pass, backpropagation is matrix multiplications end to end. You can do every one by hand, slowly and imperfectly, which is exactly why a GPU's ability to do them fast mattered so much to deep learning. 💾 Save this post!

Tom Yeh

961,186 次观看 • 1 个月前

Chains all scale the same way now. Throw activity onto an L2, spin up another rollup, let the liquidity scatter and call it progress. Cardano Community went the other direction and it’s the more telling move 👇 ◢ Relocation, not Repair An L2 doesn't fix a congested base layer. It moves the congestion to a room with a different name. You get more bridges to drain, more chains that don't talk, users spread so thin that "the ecosystem" stops meaning one thing. It demos beautifully on launch day. that's the whole appeal. ◢ Nowhere to Hide Fixing the base layer is slower and a lot less forgiving. You can't ship it and walk away. It has to survive real load while the consensus that's secured the chain for years keeps holding, and if it cracks there's no rollup to point at. Leios picked the version with no escape hatch. ◢ The flex is what stayed the same Throughput is the number people will quote but it's not the interesting decision. The interesting decision was leaving the trust model untouched, growing capacity on top of what already works instead of ripping it out and praying the replacement holds. Restraint is harder to market than a big number, which is probably why nobody markets it. ◢ Read the packaging A swordsman's name. Five phases you have to clear in order. That framing is doing work. Ship-fast teams sell the destination; this one is selling the discipline of getting there, which is a quiet way of saying judge us on the grind, not the announcement. My take: in a market that pays out to whoever is loudest, choosing the slow unglamorous path to scale is almost a contrarian bet on itself. It doesn't make leios right, that's what months of testing are for. but "we made the base layer carry more without breaking what made it trusted" is a sentence that still means something in a year. 🔗 Testnet + SPO onboarding:

Onur

19,157 次观看 • 2 个月前